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Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Anthropic's Security Governance, Risk, and Compliance (GRC) team is the connective tissue that holds the company accountable to its security commitments. We translate regulatory, customer, and voluntary obligations into controls that teams act on, and give leadership a bird's-eye view of how well we're meeting them. We're building toward a fundamentally different kind of GRC: one that directs Claude, with the right humans in the loop, to challenge and evidence the performance of controls continuously rather than through periodic audits. Within Security GRC, Compliance & Audit Programs runs the integrated audit across our frameworks and maintains the Common Control Framework, the single set of controls that the whole program is built on. This role sits in Audit & Assurance and owns the framework and the assurance view across every control domain. About the role As part of the Security Audit & Controls team,  you will own the CCF across every control domain, from access and change management to logging, encryption, and people controls: which controls we have, what each one says, how each maps to the frameworks and commitments we hold, and whether each one is actually working. You'll work with control owners and GRC Partners to draft and validate control descriptions and activities that describe reality rather than policy intent, build the monitoring that shows operating effectiveness continuously instead of once a year, and drive what monitoring finds to closure with control owners. Building with Claude is a normal part of the job: drafting and mapping controls, testing evidence, and monitoring control health, with you deciding where human judgment stays in the loop. This is an individual contributor role for someone who works well independently, writes clearly, and gets satisfaction from a control set that is accurate, tested, and trusted by auditors and engineers alike. Key responsibilities Own the Common Control Framework: the canonical control set, its mappings to SOC 2, ISO 27001/42001, HIPAA, FedRAMP, and customer commitments, and the change process for adding, retiring, or rewording controls Draft and validate control descriptions and control activities with control owners, so each control states who does what, how often, in which system, and what evidence proves it Design and run continuous monitoring of control efficacy: define the metrics and automated tests that show operating effectiveness, tune out false positives, surface failures to owners before an auditor does, and build the controls maturity model that shows where each control domain stands and what it takes to move up a level Verify remediation and carry it into steady state: GRC Partners lead remediation in their domains and control owners implement the fixes. This role advises on control design and implementation, confirms fixes against what the auditor actually asked for, and keeps one source of truth for control and finding status. Once a fix holds, it works with the partner to standardize the evidence pull and, where appropriate, automate it or build continuous Map new frameworks and commitments onto the CCF as we commit to them, and support gap assessments when a new framework, certification, product, or entity comes into scope, using the CCF as the baseline and writing the requirements for each delta Support the integrated audit and customer audits: readiness checks, walkthrough preparation, evidence request lists, and the readout of external findings back to GRC Evaluate evidence reliability, including the completeness and accuracy of system-generated reports and AI-generated evidence, and set the standard for what audit-ready evidence looks like here Build with Claude: automate control mapping, evidence testing, and monitoring, and verify machine-drafted control language before it becomes the record Minimum qualifications Several years in IT audit, security compliance, or controls assurance, including hands-on ownership of a control framework or control library across more than one framework (for example SOC 2, ISO 27001, FedRAMP, HIPAA) Working command of audit mechanics: scoping, walkthroughs, sampling, design versus operating effectiveness, deficiency evaluation, and evidence reliability Experience writing control descriptions, control activities, and test procedures that other teams and external auditors relied on Experience with continuous controls monitoring or automated evidence collection, whether you built it, ran it, or audited it Enough technical fluency to read a runbook, a configuration, or a pipeline definition and judge whether it enforces what the written control claims Clear writing, because your control language and status reports are what auditors, engineers, and leadership work from Ability to get control owners and partner teams to prioritize and close work without having authority over them Preferred qualifications Have designed or rebuilt a common controls framework and led the remapping of existing frameworks onto it Have stood up continuous controls monitoring or automated evidence programs and can speak to coverage, false-positive rates, and what changed as a result Have applied LLMs to assurance work, such as control drafting, framework mapping, evidence testing, or monitoring Have defined or assessed controls for AI systems or agents operating in production, or for home-built internal systems Have provided requirements for a homegrown GRC platform and worked with the engineers who build it You don't need to Have done everything on this list. The scarce combination this role exists for is framework ownership plus the judgment to tell whether a control actually works Write production code. The bar is fluency sufficient to read, query, and challenge Hold every certification. CISA, CISSP, or similar are welcome and not required Have prior AI-industry experience Logistics Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience. Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas. However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $345,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. The RL Scaling team works on how RL scales: what happens to throughput, stability, and learning efficiency as models get larger, episodes get longer, and compute grows by orders of magnitude, and what has to change in our algorithms and systems to keep getting returns from that scale. This role sits squarely across research and engineering. You'll develop next-generation architectures and RL algorithms, take them from a small-scale result to a frontier-scale run, and understand every place they behave differently along the way. You'll build the systems that set how fast the team can iterate: how many experiments, at what scale, and how quickly we can trust the results. And you'll work on Anthropic's largest and fastest RL runs, where the gap between a good idea and a working one is often a problem no one has solved yet. Key responsibilities Study how RL training and sampling scale with model size, context length, and compute, and find the algorithmic and systems changes that keep scaling efficient Develop next-generation model architectures and RL algorithms, and make them run efficiently at frontier scale Take promising small-scale results to frontier-scale runs, and diagnose why they behave differently when they get there, whether the cause is numerical, algorithmic, or systemic Build the experimental infrastructure that sets research velocity: fast, reproducible comparisons of architecture and algorithm variants at meaningful scale Own end-to-end performance of our largest RL runs, from research code down to the hardware Build performance and cost models for proposed architecture and algorithm changes, and use them to decide which ideas get scaled Investigate training dynamics at scale, including instabilities, divergence, and throughput regressions, and trace them to root cause Minimum qualifications Deep familiarity with modern transformer language models, including their architecture, training dynamics, and the behavior of large-scale optimization Hands-on experience training large models in a distributed setting, including the tradeoffs between data, tensor, and pipeline parallelism A track record of original technical work in ML training or systems, such as new methods, architectures, or optimizations, demonstrated through research, open-source, or production impact Ability to design rigorous experiments at scale, including baselines, ablations, and enough statistical care to trust a result that costs real compute Ability to reason quantitatively about the compute, memory, and communication costs of a model or algorithm Strong programming skills in Python and JAX or PyTorch, and comfort reading and changing code at every layer of the stack Preferred qualifications Research experience in reinforcement learning, optimization, or large-scale training, published or otherwise Experience developing RL algorithms for language models Experience with scaling laws or other quantitative models of training efficiency Experience designing or modifying transformer architectures beyond standard configurations Experience scaling training to large fleets of accelerators and debugging the problems that only appear at scale Deep understanding of numerics in large-scale training, including low-precision formats and sources of instability Familiarity with how GPU or TPU performance characteristics shape architecture and algorithm choices Experience with C++ or Rust Representative projects Characterize how a new RL algorithm's throughput and learning efficiency change from small models to frontier scale, and fix what breaks Develop a new attention variant, get it working at full scale, and measure how its quality and throughput compare to the baseline Prepare our next largest-ever RL run: find what breaks when model size, context length, and compute all grow at once, and fix it before launch Trace a loss instability that only appears past a certain scale to its root cause, and work out whether the fix belongs in the algorithm, the numerics, or the system Build a model that predicts the throughput and cost of a proposed architecture change before anyone writes the kernel The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Reinforcement learning is how Claude learns to reason, write code, and act autonomously over long horizons. At frontier scale, an RL run is an unusually demanding distributed system. Training, sampling, and environment execution run concurrently across a large fleet of accelerators and hosts, exchange data continuously, and have to keep making progress while hardware fails, load shifts, and the research changes underneath them. How well that system holds together determines how much of our compute turns into learning, and how quickly the team can try the next idea. As a Research Engineer on the Distributed Systems team within RL Engineering, you'll work on whatever part of that system is the current limit. That might be scheduling and placement, data movement between components, running large numbers of sandboxed environments, storage and checkpointing, networking, fault tolerance, autoscaling, or the observability that tells us what a run is actually doing. We're looking for generalists: engineers who can move between these layers, reason from first principles about a system they haven't seen before, and pick the problem that matters most rather than the one closest to their prior experience. Our system changes as fast as the research does, correctness under failure matters as much as throughput, and the best solutions often come from understanding the ML workload well enough to know which guarantees it actually needs. Strong candidates have built and run large distributed systems, care about getting the details right, and want to apply that experience to a workload that is very large, very heterogeneous, and changing quickly. Key responsibilities Design, build, and operate the distributed systems that run RL at scale, across training, sampling, and environment execution Find and remove whatever currently limits the system, whether it's scheduling, data movement, storage, networking, or coordination Build fault tolerance into every layer: failure detection, isolation, and recovery that keep long-running jobs making progress without human intervention Design resource management and autoscaling so that compute follows demand as a run's needs shift Build observability that makes it possible to understand what a run is doing and why it slowed down, stalled, or produced unexpected results Build automation that detects and remediates common problems, and design interfaces that let engineers and automated tools operate runs safely Work with researchers and performance engineers to make sure systems changes preserve training correctness and don't introduce subtle nondeterminism Remove classes of failure at their source through incident review, testing, and redesign, and write clear design documents for what you build Minimum qualifications Strong software engineering skills in Python and at least one systems language such as Rust, C++, or Go Experience designing, building, and operating large-scale distributed systems in production Deep understanding of distributed systems fundamentals, including consistency, coordination, consensus, failure modes, and recovery Ability to reason quantitatively about throughput, latency, and resource costs across compute, memory, storage, and network Experience debugging complex failures across many hosts and services, including failures you can't reproduce locally Strong written communication, including design documents and incident writeups Preferred qualifications Experience running ML training or inference infrastructure at scale Experience across several layers of the stack, such as scheduling, storage, networking, and orchestration Experience building schedulers, autoscalers, or resource management systems Experience with container orchestration such as Kubernetes, and with sandboxed or virtualized code execution at scale Experience with high-performance networking, RDMA, or collective communication libraries Experience building observability or automated remediation for large fleets Experience with async Python frameworks such as Trio or asyncio Familiarity with reinforcement learning or large language model training workloads Representative projects Design a scheduler that places training, sampling, and environment work across a heterogeneous cluster while respecting network topology and failure domains Build a failure detection and recovery system that lets a long-running job survive host and network failures with minimal lost work Scale environment execution substantially without increasing tail latency for the training step Design an autoscaling policy that rebalances compute across components as a run's bottleneck shifts Build a diagnostics system that explains why a run's throughput dropped and proposes a fix Trace a rare data corruption bug across many services to a race condition in a recovery path, and redesign the path so the class of bug can't recur Design the operational interface for a run so that automated tools can safely diagnose and adjust it under human oversight The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $500,000 — $850,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel Required) | San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) secures Anthropic's data center footprint; this role covers how the sites are designed and built to be secure. Much of that footprint is designed and built with partners, so a site's security is decided early: in what Anthropic hands the people who build it, and in how rigorously the delivered systems are tested against it. You'll design and specify the physical security systems for a site: perimeter and vehicle barriers, intrusion detection, video, security lighting, and the site penetrations and utility entry points that bypass them. Design firms and integrators produce the site drawings and install; you specify, review, and verify. You'll write the performance requirement and verification method behind each control, review every site design against them at each stage with redlines a design team can act on, test in the field that what was built performs as specified, and re-verify post-acceptance changes. This is a foundational role. You'll own Anthropic's physical security reference design package (typical details, reference drawings, schedules, and test procedures) in the form partners build from, and keep it current against each site's threat basis and the sites actually being built. You'll set the technical position for a site and decide what applies where; where a requirement can't be met as written, you'll engineer the compensating control and document the deviation. You'll work with the rest of DCSE, with Anthropic's design, construction, and real estate counterparts, and directly with the vendors who build to the package. We use Claude throughout our engineering workflow and expect you to as well. The same seat covers the team's security operations control rooms. You'll set their design and operational requirements and accept delivered systems against them, working day to day alongside the team's platform engineers, who own the software and compute that run in them. This role involves regular travel to data center sites. These are critical services, and this role participates in an on-call rotation for them. Key responsibilities Produce a vendor-ready design package for perimeter barriers and hostile vehicle mitigation, intrusion detection and its zoning, video coverage, security lighting matched to camera performance, and penetration protection: performance specifications, typical details and reference drawings, and device and zone schedules, written so a design firm can build to them and a test can prove them Define the per-site engineering basis: which requirements apply to a site based on its risk profile and the threats it faces, with compensating controls and documented deviations Write the acceptance criteria and test methods: the verification method behind each requirement and the evidence a site must produce to pass acceptance Set standoff, structural hardening, and site layout criteria for new designs, tied to the threat basis they derive from Run field verification: commissioning and acceptance testing of perimeter, detection, video, and lighting against performance criteria (detection coverage tests, photometric measurements, video quality checks) Write the operational and design requirements for security operations control rooms: console layout, wall versus workstation content, supervisor placement; room network, power, backup, and resilient communications to the team's segmentation and hardening baseline Own control room acceptance: factory and site acceptance criteria written before the build, then accept or reject delivered systems (video wall, consoles, cabling, fit-out) against them Minimum qualifications Have designed or specified physical security systems (perimeter barriers, intrusion detection, video, security lighting) for campus-scale sites: multiple buildings, a secured perimeter, many detection zones Read and produce construction documents (site plans, civil and electrical drawings, device schedules, submittals) using standard design and markup tools such as AutoCAD, Revit, or Bluebeam, and find what is missing as readily as what is wrong Write performance requirements that are testable: each states what must be true, how it will be verified, and what evidence shows it Have run commissioning and acceptance tests against performance criteria and rejected work that did not meet them Derive requirements from a threat basis rather than a product catalog: you can say which adversary a control stops and where the next weakest point is Have owned an engineering domain where you set the approach, chose what applied to each site, worked directly with vendors, and answered for the result Preferred qualifications Experience carrying a physical security design from construction documents through construction to acceptance testing Experience engineering the security scope of colocation or partner-delivered facilities Working knowledge of published standards for standoff, hostile vehicle mitigation, and intrusion detection zoning Photometric and video quality measurement experience Control room, AV, or network design experience: console layouts, video wall systems, resilient communications Experience using AI-assisted tooling for drafting and review as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's go-to-market engine runs on Salesforce: how leads become pipeline, how deals are tracked and forecast, how customers renew and expand, and how partners work alongside our sellers. As a Business Systems Analyst, you'll be responsible for how one of those core motions is represented in system, and a trusted partner to GTM leadership when they want to change how it works. We're looking for someone who operates at the intersection of three things: a strategist who can sit with GTM leaders and shape how they want to understand their part of the business, an analyst who can turn that into rigorous process and data design, and a builder who's comfortable enough in Salesforce to ship meaningful parts of it themselves. You can move fluidly between whiteboard, requirements doc, and admin console. You'll partner deeply with RevOps on the operating model and with our Salesforce developers on anything that needs code. Where you might sit We're hiring across several parts of the customer lifecycle. Placement depends on your background and where you can have the most impact. Opportunity Acceleration: Owns how deals are tracked, forecast, and credited in Salesforce, from stage design and forecasting to the ownership and team structures behind them. You'll partner with sales leadership to make pipeline something everyone can trust and sellers can work quickly. Lead-to-Pipeline: Owns how leads, inbound demand, and BDR outreach become qualified pipeline: lifecycle stages, routing and ownership, handoff rules, and the tools BDRs and sellers work in every day. You'll partner with BDR, marketing, and sales leadership to make the path from first touch to open opportunity faster and easier to measure. Post-Sales: Owns the systems behind renewals, expansion, and customer coverage: how post-sale opportunities are created, forecast, and worked by account management and customer success. You'll give post-sales leaders a clear, trustworthy view of the customer base and the tools to act on it. Partnerships: Owns how partner-sourced and co-sell deals are registered, attributed, and worked alongside our sellers, including the partner-facing processes and reporting leadership relies on. You'll help turn a fast-growing channel into a motion the business can measure and scale. Key responsibilities Own the design of your core funnel domain in Salesforce: lifecycle stages, process, exit and handoff criteria, key fields, and the automation and guardrails that keep the data trustworthy Partner with GTM leadership on how their motion runs and how they want to see it, and make the tradeoff calls on what teams enter versus what insight that data unlocks Partner with RevOps to systematize how GTM teams are structured, assigned, and credited: ownership, routing, coverage, splits, and the territory and role structures those depend on Operationalize the methodology in system, turning frameworks and process discipline into fields, validation, scoring, and in-context guidance that people actually use Act as data-model steward for your domain and its closest neighbors: the named approver for new fields, automation, and integrations touching those objects, and the keeper of why each one exists Build and ship declarative solutions yourself where that's the right call, and write specs clean enough that our developers can build the rest without five rounds of clarification Own the seams to the neighboring stages of the customer lifecycle (lead handoff, opportunity, quote-to-cash, renewal, partner attribution) so the experience is coherent end to end even where the build sits with another team Evaluate and configure tooling that accelerates the motion: routing, activity capture, sequencing, deal inspection, account planning Run discovery, UAT, enablement, and adoption measurement for everything you ship; help raise the bar for how BSA work is done on this team Minimum qualifications Experience in GTM/Revenue systems as a Business Systems Analyst, Sales Systems Lead, or RevOps Systems role, with real ownership of work in a core funnel domain such as lead management, opportunity and pipeline, renewals and account management, or partner channel Experience designing and rolling out a lifecycle, process model, or forecasting motion at a fast-growing company, owning it from discovery through enablement and adoption Credibility with GTM stakeholders: you've been in the pipeline review, forecast call, or planning session, and you can push back when there's a better answer Hands-on Salesforce skills, with comfort building meaningful parts of your own solution (Flow, validation, assignment and routing, page and Path design) and specs that make the handoff to developers clean Crisp communication across GTM teams, leadership, RevOps, and engineers, adjusting altitude for each Preferred qualifications 5+ years of experience in GTM/Revenue systems roles Salesforce Administrator certification Advanced Administrator, Business Analyst, or Sales Cloud Consultant certification Experience partnering with RevOps or Sales Strategy on team-structure questions (ownership, routing, splits, territory) and turning those decisions into working system design Experience across more than one part of the customer lifecycle, such as lead, opportunity, renewal, or partner Curiosity about AI-assisted systems work and eagerness to fold it into how you design, build, and document; prior hands-on use is a strong plus The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $270,000 — $315,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Riga, Latvia Workplace: fully About the Client Evotym is looking for an Operations Coordinator to work closely with our Founder and support the day-to-day operations. Evotym is an international FinTech recruitment agency founded in Riga, Latvia. We work with companies across the financial technology ecosystem and operate in a fast-moving, international environment. We're looking for someone who can bring structure, energy, and ownership to the team — and who genuinely enjoys making things work better. Your role will be broad and dynamic. You will help the Founder and the wider team keep projects, processes, and day-to-day operations moving forward. Role Overview This is a great opportunity for an ambitious early-career professional who wants to gain hands-on experience across operations, project management, research, AI & automation, marketing, and business administration while working directly with the CEO. You might currently be a Project Coordinator, Operations Assistant, Marketing Coordinator, Business Assistant, Recruitment Coordinator, Office Manager, Junior Project Manager, or a student/recent graduate with 1+ years of relevant hands-on experience. You don't need years of experience in operations. We care much more about how you think and work: being organised, proactive, curious, reliable, and comfortable figuring things out independently. Key Responsibilities Coordinate internal projects and make sure tasks, deadlines, and follow-ups don't get lost Work directly with the Founder on business and operational priorities Turn ideas and loosely defined requests into clear action plans and next steps Conduct research, compare options, and prepare short summaries and recommendations Coordinate with team members, contractors, partners, and external service providers Support business administration, documentation, invoices, contracts, banking-related matters, and other operational tasks Help organise business travel, conferences, meetings, and events Maintain project and task tracking in Asana Identify processes that could be improved, simplified, or automated Use ChatGPT, Claude, and other AI tools to make everyday work faster and more efficient Support selected marketing, LinkedIn, content, community, and partnership initiatives Help with occasional personal and organisational requests for the Founder Requirements 1+ year of experience as a Project Coordinator, Operations Assistant, Marketing Coordinator, Business Assistant, Recruitment Coordinator, Office Manager, Junior Project Manager, or other. Previous experience working with CEO/another C-level Executive is an advantage. Experience with Asana, AI tools, social media/content, recruitment, FinTech, finance, or project management would be an advantage. You can take a broad request, structure it, and turn it into concrete next steps. High level of independence and ownership. Excellent research skills. Good English and native Russian. Key Soft Skills High level of independence and ownership. Ability to structure large amounts of information concisely. Attention to detail and ability to manage multiple tasks. Speed and independence in managing tasks. Capability to handle multiple priorities at once. Discretion and confidentiality. What We Offer Close work with the Founder of a successful business. Collaborative and transparent team culture. High-impact role in a scaling fintech company. Recognition of personal milestones and achievements. Fully remote job from Riga.

Location: San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking an experienced public opinion researcher to build and expand Anthropic's in-house polling and research function. This role will be fundamental to understanding how key audiences — from policymakers and third-party groups to the general public — perceive and respond to Anthropic's policy positions, messages, and campaigns. This is a foundational role: you'll establish the research function from the ground up, with high autonomy and limited precedent. The Central Policy team sits at the operational heart of Anthropic's policy function — distinct from government relations and communications, but essential to enabling both. You'll work cross-functionally to ensure our policy and communications strategy is grounded in a rigorous understanding of stakeholder sentiment. The polling insights you generate will directly feed into high-visibility campaigns and will be a key asset in our policy efforts in Washington and beyond. Anthropic is equal parts research lab, policy think-tank, and technology startup. We care deeply about the safe development of AI systems and build partnerships with governments through proactive, opinionated, substantive policy conversations. This role offers a unique opportunity to be at the forefront of AI policy, bringing rigorous research discipline to policy strategy. Success in this role means establishing trusted relationships with leading polling firms around the world, delivering high-quality research on a regular cadence, and becoming the internal expert on how key audiences perceive AI, Anthropic, and Anthropic's positions and messages. You'll translate polling insights into strategic recommendations that measurably improve campaign effectiveness, and build scalable processes that allow the function to grow efficiently as demand increases. Key responsibilities Develop a comprehensive strategy for our in-house political research function that aligns with Anthropic's policy goals Identify, evaluate, and establish relationships with leading research and polling firms, ensuring coverage across demographics, geographies, and political perspectives Conduct detailed, proactive research to test core messages, policy proposals, and campaign themes, and to evaluate Anthropic's brand perception and performance Execute rapid-response polling to quickly assess Anthropic's messaging strategy in response to external events, policymaker actions, competitive developments, or emerging opportunities Work with external affairs colleagues (federal, state, and international) and policy communications to identify research priorities, interpret findings, and translate insights into actionable strategic recommendations Develop and maintain a knowledge management system for polling data, insights, and recommendations that ensures findings are accessible and actionable Manage polling vendors at scale, including vendor performance management Participate in strategy sessions and provide thought partnership on the design of messages, policy proposals, and campaigns ahead of polling and testing Create clear, compelling deliverables that distill polling findings into insights and recommendations Identify opportunities to build and scale the polling function over time, including staffing needs, process improvements, and capability expansion Track and report on the impact and utility of research, measuring how insights translate into more effective campaigns and strategic decisions Minimum qualifications Experience designing and executing public opinion research, including survey and questionnaire design, sampling approaches, and message testing Ability to analyze quantitative and qualitative polling data and translate findings into clear, decision-ready written recommendations Experience selecting, briefing, and managing external polling or research vendors Strong writing and presentation skills, including distilling complex research for senior, non-technical audiences Preferred qualifications 8+ years of professional experience in political or public opinion research, ideally spanning multiple campaign cycles and policy environments Corporate public affairs experience, ideally in a highly scrutinized or regulated industry Strategic thinking that spots emergent issues, identifies and tests the right messages, and translates those insights into tactical recommendations A track record of building relationships with vendors, external experts, and complex stakeholder ecosystems Strong organizational skills, with the ability to manage multiple projects simultaneously, maintain clear priorities, and deliver on tight timelines Comfort operating in ambiguous environments, taking ownership of problems, and proactively driving initiatives with limited precedent A resourceful, collaborative working style and genuine commitment to being a strong teammate Passion for AI policy and alignment with Anthropic's safety mission and commitment to responsible AI development The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $230,000 — $265,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: As a Field Executive Architect, you will serve as Anthropic's senior technical voice with our most strategic customers. You'll engage directly with C-suite executives and senior technical leaders at the world's largest enterprises to understand their business, align stakeholders around a clear vision for how AI fits into their strategy, and create momentum toward adoption of Anthropic's products. This is not a hands-on-keyboard engineering role. Your job is to walk into a room full of executives, quickly understand their business and technical landscape, and help them see a clear path forward with Claude. You'll then partner with Sales and Applied AI teams to ensure that vision translates into execution -- checking in on high-momentum accounts, maintaining executive relationships, and keeping deals on track. Internally, you'll serve as a sponsor for enterprise customer needs, working with Product to ensure that what matters most to our largest accounts is heard and prioritized. You'll bring deep experience in enterprise technology and a track record of operating at the intersection of business strategy and technical execution. Whether you've been a CTO, VP of Engineering, Field CTO, or a world-class senior technical salesperson, what matters is that you've seen how large organizations make technology decisions and can meet executives where they are -- with credibility, clarity, and conviction. Responsibilities: Engage directly with C-suite and senior technical leaders at Anthropic's largest and most strategic accounts, aligning business and technical stakeholders around a clear vision for AI adoption Prepare for and lead high-stakes customer engagements -- executive briefings, EBCs, on-site workshops -- that change the trajectory of key accounts at critical inflection points Partner with Sales and Applied AI teams before and after engagements to game plan approach, debrief on outcomes, and ensure the vision carries through to execution Lean in on high-momentum accounts after initial engagement, maintaining executive relationships, providing strategic guidance to the Sales and Applied AI teams, and sustaining deal momentum Serve as an internal sponsor for enterprise customer needs, translating field feedback into clear priorities for Product and ensuring the most important enterprise requirements are heard and acted on Bridge the gap between our field organization and Product org -- helping each side understand the other's priorities, constraints, and roadmap Travel regularly to customer sites for executive engagements, workshops, and strategic account meetings You may be a good fit if you have: 15+ years of experience in enterprise technology, with significant time spent in senior technical leadership or senior technical sales roles (CTO, VP of Engineering, Chief Architect, Field CTO, or similar) A track record of engaging credibly with C-suite executives and senior technical leaders at large enterprises -- you can hold the room and earn trust quickly Deep understanding of how large organizations evaluate, buy, and scale technology -- you've seen the inside of these decisions from a leadership seat or from the sales side of the table Enough technical depth to understand modern AI systems and their enterprise applications, and enough business acumen to connect technical capabilities to business outcomes Experience translating between technical and business audiences -- you can make complex topics clear and compelling for both Strong opinions about what makes enterprise technology adoption succeed or fail, informed by having led or closely advised these efforts The ability to navigate ambiguity and move fast in a rapidly evolving market -- you're comfortable operating without a detailed playbook and building the plane while flying it A collaborative mindset -- sales at Anthropic is a team sport Excitement about AI's potential to transform how enterprises operate, and a genuine desire to help customers succeed with it Willingness to travel regularly for customer engagements The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $400,000 — $500,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Tasks: — Lead and execute core 0-to-1 initiatives in cutting-edge domains such as Agentic AI. — Translate high-level strategic vision into concrete execution roadmaps, driving rapid implementation from prototype to production. — Architect scalable solutions and drive critical milestones to position the new department for rapid growth and potentially a spin-off to attract institutional backing. Requirements: — Based in Europe or the Americas (or open to relocate/remote arrangements). — High-agency builder mindset, with proven domain expertise and the drive to take extreme end-to-end ownership. — Excellent verbal and written communication skills in English. Conditions: — 100% remote work. — Full-time employment. Additional information: — Maximum ownership: Complete autonomy to architect systems, drive strategy, and build from 0 to 1 without corporate red tape. — High-growth environment focused on strong market validation and scalable traction. — Elite team: Report directly to the department founder and collaborate with a world-class team. — Competitive compensation with equity upside.

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Data Center Security Engineering (DCSE) owns physical security across Anthropic's data center footprint: the sites, the hardware inside them, and the supply chain that delivers it. The Security Fusion Platform is where physical security signals from across that footprint are correlated and put in front of the analysts who act on them. It carries continuous monitoring, audit evidence, metrics, and analyst response, along with the classification and analytics pipelines that turn sensor data into events. You'll build and own the platform analysts work from. This is a foundational role. You'll build the software platform that carries a signal from source to analyst decision, ship its first versions, and keep them running in production. The sensors and systems at each site belong to other DCSE engineers; you define the event contract their owners deliver to, and you build the classification and analytics pipelines that run over what those sources produce. Physical security systems engineers own the operations spaces; you own the software that runs in them. You'll work alongside engineers focused on the sites themselves. What you lead, you own end to end: the design, the technical approach, and the result in production. You'll work with external vendors and integrators, setting requirements and acceptance criteria for what you own and deciding what the team builds itself. We use Claude throughout our engineering workflow and expect you to as well. This role involves regular travel to data center sites. No security clearance is required. These are critical services, and you'll take part in on-call for them. Key responsibilities Design and build the event bus and normalized event schema: source identity, sequencing, health state, and the adapter contract that owners of each sensor and system feed build to, plus adapters where needed Build correlation and alerting: the rules and services that turn events from independent sources into alerts an analyst can act on Build the classification and analytics pipelines: computer vision and multi-sensor fusion, with results landing on the event bus Build analyst surfaces: the queue, escalation tooling, dashboards, camera viewers, and video wall content a 24/7 watch works from, plus video analytics integration so camera streams arrive on the bus as events Deliver audit evidence: durable, tamper-evident event history, evidence exports, and the retention and access controls around them Instrument metrics and self-monitoring: detection rates, nuisance ratios, alert aging, time to resolve; heartbeats and loss-of-telemetry alarms on every feed, tested fail-secure behavior, and change audit on every rule Deploy across sites: site-local components, central services, and the sync that keeps configuration, rules, and state consistent, then commission each site and hand over to the analysts Specify the compute the platform runs on (servers, storage, and the platform's network segment) to the team's segmentation and hardening baseline Write requirements and acceptance criteria for what vendors and integrators deliver, review deliverables against them, and make the call on accepting or rejecting the work Minimum qualifications Have built and run event-driven backend systems in production Are proficient in at least one backend language such as Python, Go, or Rust, and have worked with a message bus or event streaming system such as Kafka Have owned a system end to end: set the design, made the tradeoffs, shipped it, and answered for it in production Have integrated with external systems you did not control (vendor APIs, on-prem appliances, video platforms, building systems) and designed for a life beyond any one vendor Have directed vendor or integrator work: written requirements and acceptance criteria, reviewed deliverables against them, and decided what gets accepted Design for the failure you won't see coming (a silent feed, a lost network path, a replayed event, a de-tuned rule), know how your system behaves when a source lies or goes quiet, and test for it Build tools for people who use them under pressure and iterate with those operators Preferred qualifications Experience building or operating a security operations platform (SOC, physical security operations, or the detection engineering behind one) Experience building ML or computer vision inference pipelines over video and sensor streams PSIM (physical security information management) or VMS (video management system) integration experience, or familiarity with physical access control and building systems data Experience producing evidence for auditors or assessors: log integrity, retention, chain of custody Experience using AI-assisted development tooling as a core part of your workflow The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Worldwide Social Discovery Group (SDG) is a group of social discovery companies. SDG solves the problems of loneliness, isolation, and disconnection - transforming virtual intimacy into the new normal. SDG’s products redefine the way people interact and connect with one another. Our portfolio includes social entertainment platforms designed to connect people online across different cultures and regions of the world. SDG invests in social discovery and IT startups around the world directly or via VC funds. Among our investments were Patreon, Open AI, Clubhouse, Coursera, Data.ai , Flo, Academia.edu , and many others. We bring together a team of like-minded people and IT professionals who specialize in creating and developing globally impactful social discovery products. Our international team of digital nomads works remotely from all over the world. We’re proud to be a two-time “Great Place to Work” winner (USA & Japan, 2024–2025) and a Top-5 Company for Work-From-Anywhere Jobs (FlexJobs, 2025). We are looking for Head of Design . Your main tasks will be: Own the end-to-end the product's user experience — from ad creative and landing pages through onboarding, avatar selection, chat, media generation and retention loops — holding the whole journey consistent, not just individual screens. Grow product metrics through design: conversion to purchase, retention, LTV. Form hypotheses, prioritize them, validate through A/B tests and see them through to release. Set a single design direction and evolve the design system: UI, UX patterns, character visual style, generated content, animation and UX copy. Lead the design team (2 product designers, a UX writer, a researcher), build the processes and the cross-functional work with product, analytics, marketing and engineering. Turn research, user interviews and support insights into concrete roadmap initiatives aligned with business priorities. We expect from you: 3+ years leading a design team of 3 or more in B2C daily-use products — AI companions, social, dating, health & fitness, edtech, messengers; products with 2M+ MAU or $50M+ in revenue. Cases with measurable design impact on metrics: what you changed, why, and how it moved CR, retention or LTV — with before and after numbers. Strong product design expertise: UX, UI, user flows, information architecture, prototyping; confident in Figma; experience building and maintaining design systems. Proven cross-functional work with product and analytics: A/B testing, prioritization frameworks (RICE), data-driven decisions — design as part of the product, not a separate function. A strong visual eye and taste paired with an analytical mind; English at C1 or above. What do we offer: REMOTE OPPORTUNITY to work full-time; The initial pay level or pay range for this role will be shared with candidates during the recruitment process and before the commencement of employment; Vacation 28 calendar days per year; 7 wellness days per year (time off) that can be used to deal with household issues, to lie down and recover without taking sick leave; Bonuses up to $5000 for recommending successful applicants for positions in the company; 50% payment for professional training, international conferences, and meetings; Corporate discount for English lessons; ​ Health benefits. According to the paychecks, if you are not eligible for corporate medical insurance, the company will compensate you with up to $ 1,000 gross per year per employee. This can be spent on self-purchase of health insurance or on doctor’s fees for yourself and close relatives (spouse, children); ​ Workplace organization. The company provides all employees with an equipped workplace and all the necessary equipment (table, armchair, wifi, etc.) in our offices or co-working locations. In the other locations, the company provides reimbursement of workplace costs up to $ 1000 gross once every 3 years, according to the paychecks. This money can be spent on the rent of the co-working room, on equipping the working place at home (desk, chair, Internet, etc.) during those 3 years; Internal gamified gratitude system: receive bonuses from colleagues and exchange them for our merchandise, team building activities, massage certificates, etc. Sounds good? Join us now!

Location: Russia; Moscow; Perm Workplace: remote About Xsolla Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. About the Role We are hiring a Staff Software Engineer to own the smart wallet and account abstraction layer of XsollaZK, Xsolla's Web3 platform on a zkSync-based L2. This is an individual contributor role with a large technical scope. You are the technical anchor for how millions of players get an on-chain account they never have to think about. The product. Every player who signs in with Xsolla ID receives a deterministic, non-custodial smart account. The account is derived from their identity claim, is identical on every device, and its private keys never leave the client. It is not a separate wallet screen: it is the player's inventory. It backs: minting and gifting; trading on our Bazaar marketplace; Merkle-based reward airdrops; gas sponsorship; an in-app dApp browser that exposes the same signer to third-party applications through an EIP-1193 provider. Responsibilities The technical strategy and architecture of the smart wallet platform: account model, signing, session management and gas abstraction at scale The smart account and permissioning model, evolved to meet both product and compliance needs The security model where our signer meets third-party applications: what a player is actually approving, and proof that the UI shows it The custody and recovery roadmap, from today's interim mechanisms (including raw key export) to MPC -based custody Cross-team technical decisions on account architecture, SDK contracts, data modeling and platform reliability, with buy-in from the wallet, marketplace, SDK, mobile and security teams Engineering standards in the Web3 domain Production escalations in the wallet and account abstraction domain WHAT YOU WILL DO Design and evolve the ERC -4337 user operation lifecycle (prepare → sign → submit → confirm), EIP -7702 delegation, deterministic address derivation from identity, and the session-key and permission primitives (including origin-bound Smart Sessions) that let players act without a prompt on every transaction Set the paymaster and gas-sponsorship strategy: what we sponsor, how we meter and cap it, how we defend it from abuse, and how it degrades when sponsorship is unavailable Define EIP -1193 / EIP -6963 provider behavior, origin-bound and policy-versioned sessions, trust tiers, and the transaction and signature confirmation flow Design recovery paths (passkeys, guardians, social recovery) that a non-crypto-native player can complete without losing assets Identify systemic risks (key management, signature phishing, reorgs and indexer staleness, bundler and RPC dependencies, contract upgrade paths) and lead initiatives that resolve them before they become incidents Write RFCs and design docs; review critical code, contracts and designs Work with product, security, legal and infra teams to align on the roadmap and turn business and regulatory needs into well-scoped technical plans Create leverage for the engineering org through documentation, tooling and mentorship Serve as the escalation point for complex production issues: a stuck user operation, a drained paymaster, a signing prompt a player didn't understand Set up and maintain AI tooling in the repositories (Claude Code, Codex, Cursor: rules, context, harness) so the team uses it effectively REQUIRED Experience 8+ years of engineering in the Ethereum ecosystem working with crypto wallets and smart wallets Designing or operating a production smart wallet or account abstraction system serving real users and real value Shipping and operating systems where a bug meant lost funds. You can talk concretely about the guardrails, reviews and rollback paths you put in place Account abstraction and smart wallets ERC -4337 in depth: EntryPoint (v0.6 through v0.8), the UserOperation lifecycle, bundler and paymaster roles, validation rules ( ERC -7562), gas estimation and its failure modes, counterfactual deployment, signature validation for undeployed accounts ( ERC -6492) EIP -7702 and the post-Pectra landscape: EOA delegation, its interaction with EntryPoint v0.8, and the risks it introduces (residual key authority, delegation phishing, storage collisions) Building on or extending production smart account implementations; modular account standards ( ERC -7579 / ERC -6900) Session keys and delegated permissions: scoped, time-limited, policy-bound authority; TTLs and contract allowlists, origin binding, permission revocation; ERC -7710 / ERC -7715 Signature schemes and wallet interfaces: EIP -712 typed data, ERC -1271 contract signatures, WebAuthn / passkey (P-256) signers; EIP -1193, EIP -6963, EIP -5792 batched calls, ERC -7677 paymaster interfaces Smart contracts and EVM Solidity and the EVM : reading, reviewing and writing account, paymaster and module contracts; gas-aware design; upgradeability and migration patterns; working effectively with external auditors L2 specifics and their effect on wallet design: native account abstraction on zkSync-family chains, transaction and fee models, finality and reorg behavior, RPC and indexer semantics Backend Go: idiomatic code, concurrency patterns, performance profiling TypeScript and SDK design: client-side SDK surfaces that internal and external teams build on Distributed systems and their trade-offs (consistency, availability, failure modes); reconciling off-chain state against an authoritative on-chain result Data and infrastructure PostgreSQL: schema design, query optimization, migrations at scale Kubernetes: deploying, operating and debugging services Asynchronous messaging and event-driven design (Kafka or NATS ): consumer groups, at-least-once delivery Git, CI/CD Security Key management in production: platform secure storage (Keychain / Keystore), HSMs, MPC or threshold signing, and the operational discipline around each Wallet threat modeling: signature and delegation phishing, malicious dApp origins, replay and cross-chain replay, token approval abuse, paymaster griefing and DoS Leadership Leading multi-quarter technical initiatives across teams Influencing architecture and standards beyond your immediate team RFCs and design docs that stand on their own and are actionable without you in the room AI-assisted engineering Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for development and review, including configuring them for a repository English English at C1 level Nice to Have Hands-on experience with ZK Stack and zk -rollups Hands-on experience with embedded and ecosystem wallet and AA infrastructure technologies (thirdweb, Privy, Dynamic, Turnkey, Pimlico, Alchemy, Biconomy, ZeroDev, Safe{Core}), with clear views on build versus buy MPC / threshold custody, social recovery or guardian-based recovery in a consumer product NFT and token infrastructure at scale: ERC -721 / ERC -1155 / ERC -20 mechanics, marketplace contracts, Merkle-based airdrop and claim distribution, chain indexing services Contributions to open-source wallet, security or identity projects, including authoring or reviewing ERC / EIP standards Compliance requirements for crypto consumer products: KYC / AML , geofencing, MiCA , SOC 2, ISO 27001, GDPR data minimization, audit logging Identity and auth integration for wallet derivation: OAuth 2.0 / OIDC , JWT verification, token scoping Platform or infrastructure engineering: building systems other engineers build on Owning a mobile wallet surface: React Native / Expo, WebView provider injection, native signing UI Gaming industry experience: platforms for game developers, publishers or players How We Work Decisions in writing. Significant technical decisions are written up as an RFC or ADR that lays out the options and trade-offs. We work across time zones, so a design has to stand on its own. AI is part of everyday engineering. We use AI coding tools for development and review, and we treat configuring them for a codebase as real engineering work. HOW WE HIRE Intro call. Your background, your motivation and the role. Technical interview. Built directly on the What you will own and Required sections above. We won't ask about anything this posting doesn't promise. System design. You design part of a wallet or account abstraction platform end to end and walk us through the trade-offs. Bar raiser. An engineer from outside the hiring team checks that you raise the overall engineering bar. Benefits We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play. EMPLOYMENT DETAILS Location: Remote  Employment Type: Full-time Schedule: 10:00–19:00 (flexible)

Location: Europe; Poland; Remote - Slovakia; Remote — Romania; Lithuania; Latvia; Ukraine; Estonia; Limassol; Slovenia Workplace: Remote Remote | EU/EEA | Regulated Crypto & Payments Company | Part-time B2B Consultancy About the Client Our client is a global fintech company operating at the intersection of crypto and traditional payments. It serves millions of users worldwide through two business lines: a B2C retail platform for buying, selling, and swapping crypto, and B2B infrastructure providing on/off-ramp APIs, payouts, and compliance infrastructure for fintechs, wallets, and platforms. The company's EU operating entity holds a MiCA CASP authorisation and a Payment Institution licence under PSD2, serving EU customers and powering a regulated B2B platform that fintechs, neobanks, PSPs, and Web3 companies build on - under the company's licences. Its control environment is part of the product, not back-office overhead. About the Role The company is looking for an Internal Auditor to run the third line of defence for its EU-licensed entity. This is not a compliance role and not a monitoring role with an audit title. You audit Compliance controls - you do not execute them. You report functionally to the Management Board, you set your own severity ratings, and you deliver findings to the people who run the company, including when the finding is about them. The function already exists. The Charter, Audit Universe, Internal Audit Plan and findings register are in place and Board-approved. This is not a rebuild of the methodology - it is delivering the plan with rigour, keeping the register alive and closed out with evidence, and putting the Board and the supervisor in a position where the control environment can be answered from the file. - What You'll Do Own and maintain the risk-based Internal Audit Plan across MiCA CASP and PSD2 PI obligations, AML/KYC/CTF controls, ICT and security (DORA), custody and segregation of client assets, safeguarding of client funds, outsourcing and third-party risk, governance and financial controls. - Execute engagements end-to-end - design the programme, select samples, test controls, rate severity and regulatory impact. - Write Board-ready audit reports with findings that hold up under challenge and recommendations someone can actually act on. - Obtain remediation plans with named owners and deadlines; track and verify closure against evidence, not assertion. - Present findings and remediation status to the Management Board - quarterly updates and the annual Internal Audit Report. - Deliver the annual independent AML/CFT audit and the DORA ICT framework audit and follow-up. - Scope, direct, and challenge external specialists where an engagement needs deep technical testing. - Maintain the audit evidence that supports regulatory supervisory reviews and inspections. What We're Looking For Required - 5+ years of internal audit or internal control experience in a regulated financial services entity - bank, payment institution, EMI, investment firm, insurer, regulated fintech or crypto/VASP. Unregulated-only experience will not be considered. - Hands-on audit experience with at least one fintech, payment institution, EMI, crypto exchange or VASP - execution, not advisory theory. - Working knowledge of at least two of MiCA, PSD2, AMLD5/6 and DORA, with the ability to turn a regulatory obligation into a test programme. - Strong understanding of AML/KYC/CTF frameworks and how to audit their effectiveness. - Evidence of independence in practice - critical findings delivered to senior management or a Board and held under challenge. - Ability to run an engagement unsupervised and to make and defend a professional judgement on control severity. - Sufficient ICT and information security audit literacy to scope a DORA engagement and to direct and challenge an external technical specialist. - Fluent professional English - reports go to the Board and to the regulator as written. - Hands-on use of AI tools in audit work - planning, analysis, testing or reporting - with concrete examples. - Right to work and tax residence in the EU/EEA, with eligibility to be appointed to an internal control function of a licensed entity. Nice to Have - MiCA CASP post-authorisation audit experience. - PSD2 / EMI safeguarding, own funds and scheme-compliance audit experience. - Deep ICT / information security audit capability, including DLT infrastructure, wallet security and key management. - DORA operational resilience, outsourcing and third-party risk audit experience. - Custody and segregation-of-client-assets audit experience. - Travel rule (FATF / EU TFR) audit experience. - Experience with a Baltic or other EU financial supervisor. - Board- or regulator-facing communication experience. - CIA, CISA, ACCA or an EU-recognised internal audit qualification. - Russian or Latvian. What Makes This Role Different - This role is for auditors who want real independence, not a compliance review with an audit title. - You inherit a working function - Charter, plan, universe, and findings register already exist and are Board-approved - and you run it, not rebuild it from scratch. - You report functionally to the Board, set your own severity ratings, and deliver findings directly to the people who can act on them, including senior leadership. - You'll work across one of the more complex dual-licensed perimeters in Europe (MiCA CASP + PSD2 PI), with direct Board access and budget for external technical specialists where needed. Working Environment - Remote across the EU/EEA, with periodic in-person days at the company's EU office (roughly quarterly, or around Board meetings). - Part-time engagement (~0.5 FTE), B2B consultancy contract. - Functional reporting to the Management Board; no team, no review layer - full ownership of the function. - Scheduled checkpoints at scope memo, draft report and Board reporting stages; no involvement from management in fieldwork, findings or ratings.

Location: Limassol, Cyprus Workplace: on-site Mayflower is a technology company building high-load products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience. We are looking for a Lead ML Engineer to own a new ML stream focused on fast delivery of applied machine learning solutions across different product and business domains. The stream will work with a broad range of ML challenges. Some initiatives may be relatively small and delivered within a few weeks, while others may prove their value and grow into larger dedicated projects. This role combines hands-on ML engineering with end-to-end technical delivery ownership. You will receive product problems and expected outcomes from Product or internal stakeholders, clarify the technical requirements and constraints, define the implementation approach, coordinate execution within the stream, and bring solutions to production readiness and launch. This is a highly hands-on role. The stream will not have a dedicated software engineer for every initiative, so we expect Data Scientists and ML Engineers to be comfortable working beyond experimentation and contributing directly to production code. The role is not tied to a single ML domain. We value strong ML fundamentals, engineering skills, pragmatism, and the ability to quickly understand new problem areas more than deep specialization in one particular class of models. Job Responsibilities Technical Delivery Ownership Turn product and business problems into concrete ML implementation plans. Clarify requirements, constraints, available data, integrations, and success criteria together with Product and relevant stakeholders. Define technical scope, milestones, dependencies, risks, and delivery estimates. Select appropriate ML approaches and determine the fastest reliable way to validate and implement them. Drive technical delivery through experimentation, implementation, integration, deployment, and launch readiness. Keep delivery on track, proactively identify blockers, and coordinate dependencies with other teams. Provide Product with clear technical options, trade-offs, estimates, risks, and experiment results required for product decisions. Support production rollout and iteration based on observed results. Hands-on ML & Engineering Design, train, evaluate, and deploy ML models across different domains and problem types. Write production-quality Python and contribute directly to implementation. Build APIs, batch jobs, data-processing pipelines, and ML services required to deliver solutions where appropriate. Work with classical ML, deep learning, and foundation-model-based approaches depending on the problem. Process and transform large production datasets using Python and SQL. Integrate models into existing production systems. Implement appropriate testing, monitoring, logging, and observability for delivered ML solutions. Work within the shared ML infrastructure, architecture, and engineering practices used across the company. Collaborate with Data Science, Backend, Data Engineering, and MLOps specialists when deeper domain expertise or infrastructure changes are required. Stream Execution Break initiatives down into concrete technical tasks and coordinate execution within the stream. Coordinate the work of Data Scientists and ML Engineers contributing to stream initiatives. Review technical approaches, experiments, and implementation. Keep the team focused on the agreed scope, priorities, and delivery timeline. Identify technical risks and dependencies early and drive them to resolution. Escalate architectural, infrastructure, or methodological questions when broader alignment is required. Help prepare successful initiatives for scaling or transition into longer-term ownership if they grow beyond the scope of the stream. Cross-functional Collaboration Work closely with Product throughout the delivery lifecycle. Independently gather the technical details and constraints required to execute on a product request. Communicate estimates, dependencies, technical trade-offs, and delivery status clearly. Work directly with Engineering and other internal teams to unblock implementation. Challenge technically unclear, contradictory, or infeasible requirements and propose practical alternatives. You’ll thrive here if you have 5+ years of commercial experience in Machine Learning, Data Science, or ML Engineering. Strong hands-on Python programming and software engineering skills. Experience taking ML solutions from a product requirement through experimentation, implementation, integration, and production. Strong understanding of machine learning methods, statistics, experimentation, and model evaluation. Experience writing maintainable production code rather than working exclusively in notebooks. Experience building APIs, services, batch processing, or data pipelines. Strong SQL skills and experience working with large production datasets. Practical experience with Docker and production deployment environments. Ability to turn partially defined problems into concrete technical plans. Ability to estimate work, identify dependencies and risks, and drive technical execution against a timeline. Experience owning technical delivery involving several contributors and coordinating work across dependencies. Experience reviewing code and technical approaches. Ability to work effectively within established engineering and ML practices while independently owning delivery within a stream. Strong communication skills and the ability to work directly with Product and technical stakeholders. Ability to balance speed and engineering quality: validate ideas quickly when uncertainty is high and build robust solutions when moving towards production. Nice to Have Previous experience as a Tech Lead, Stream Lead, or technical owner of ML initiatives. Experience with Kubernetes and CI/CD. Experience with Kafka or other streaming platforms. Experience with Airflow, MLflow, experiment tracking, model monitoring, or similar tooling. Experience building real-time or high-load ML services. Experience with FastAPI or similar Python service frameworks. Experience across several ML domains, such as recommendation systems, ranking, NLP/LLMs, Computer Vision, anomaly detection, forecasting, or classification. Experience with LLM inference, fine-tuning or other GenAI systems. Experience in teams where Data Scientists and ML Engineers own a substantial part of production implementation themselves.

OnTheGoSystems, the company behind WPML, Toolset, and PTC, is looking for a hands-on, AI-native marketer to take ownership of marketing and help shape its direction. AI is a core part of their work, and the candidate should already use AI agents, automation, integrations, and structured workflows to accomplish real marketing tasks and demonstrate achievements with them. This is a technical role involving working with their own analytics, newsletter, and marketing automation systems, requiring comfort with technical tools, setting up local development environments, and using tools like Claude to navigate technical tasks. The candidate will not join an established marketing team or follow a fixed playbook but will have the freedom to engage with clients, understand the business, identify strong opportunities, and decide marketing priorities. Задачи: — Own several marketing areas including SEO/GEO/AEO, content and collaborations with partners, authors, and bloggers, marketing to existing customers (retention and expansion), paid advertising, client analytics, and other identified marketing opportunities. — Work hands-on from opportunity identification through execution, measurement, and improvement. — In the first weeks, learn products, industry, competitors, and ecosystem; speak directly with customers to understand their needs; analyze data and existing activities; identify impactful marketing opportunities; and build a concrete plan for owned areas. Требования: — Experience using AI agents, automation, and advanced AI workflows in everyday marketing work with demonstrable results. — Hands-on and comfortable with the technical side of marketing. — Curiosity and ability to understand customers and business before proposing solutions. — Ability to work across different marketing areas and turn ideas into action. — Understanding of how marketing connects to business results. — Experience marketing technical products, ideally software, SaaS, WordPress, or similar. — Ability to work independently and drive progress without detailed instructions. — Comfortable working in a dynamic environment with changing priorities and undefined tasks. Условия: — Profitable, self-funded product company growing since 2007. — WPML powers over 1.5 million websites worldwide. — Real ownership and freedom to build marketing approach, work directly with CEO and product teams, experiment with AI, and implement marketing initiatives. — Supportive work environment with perks and benefits supporting work and life. — Flexibility of remote work. If excited about building marketing with AI, hands-on work, and shaping future marketing, the company invites applications.

Location: Seoul, South Korea About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Partners Solutions Architect on the Applied AI team at Anthropic, you will be a Pre-Sales architect focused on cultivating technical relationships with our Global and Regional System Integrators (GSIs/RSIs), and our cloud partners (AWS and GCP). You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy. Key Responsibilities Strategic Technical Partnership : Be a technical thought partner to the Anthropic GTM partnerships team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities. Embed with GSI and cloud partner technical teams to enable their AI practices, support troubleshooting, evangelize Anthropic in their developer communities, and serve as an escalation point for complex technical issues. Joint Solution Development: Collaborate with partners to identify high value industry-specific GenAI applications, develop joint solutions and codify reference architectures / best practices to accelerate time to deployment Customer Deal Support: Intervene directly to unblock strategic customer deals where partners are the primary delivery vehicle, providing deep technical expertise and solution architecture guidance. Partner Ecosystem & Events : Represent Anthropic at partner events such as GSI customer workshops, AWS summits, and industry conferences. Lead or support partner-specific developer events, hackathons, and technical enablement sessions, especially for technically native communities. Product Feedback: Validate and gather feedback on Anthropic's products and offerings, especially as they relate to partner use cases and deployment patterns, and deliver this feedback to relevant Anthropic teams to inform product roadmap and partner strategy. Preferred qualifications 5+ years of experience in technical customer-facing/partner-facing roles such as Solutions Architect, Sales Engineer, Partner Sales Engineer, Technical Account Manager Track record of successfully partnering with GSIs and/or cloud providers to solve complex technical challenges, from initial solution design through customer delivery Exceptional ability to build relationships with and communicate technical concepts to diverse stakeholders to include C-suite executives, engineering & IT teams, and more Strong presentation & technical communication skills with the ability to translate requirements between technical and business stakeholders Experience designing scalable cloud architectures and integrating with enterprise systems Familiarity with common LLM frameworks and tools or a background in machine learning or data science Excitement for engaging in cross-organizational collaboration, working through trade-offs, and balancing competing priorities A love of teaching, mentoring, and helping others succeed Passion for thinking creatively about how to use technology in a way that is safe and beneficial, and ultimately furthers the goal of advancing safe AI systems Fluent in Korean and English Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team, focused on using Claude to speed up protein and small-molecule design. You'll work with research partners to apply modern design and structure models to real discovery problems, and build the agents and skills that turn those tools into end-to-end workflows. This role is about applying design models, not building new ones. Responsibilities Work with research partners on protein and molecular design end-to-end with Claude, from advising, to prototyping, to writing production code. Work in a design–make–test loop with wet-lab partners (e.g. antibody-repertoire mining, MD prep / trajectory analysis at proteome scale) and turn the expert steps into reusable agents/skills. Build agents and skills that wrap design and structure tools into end-to-end workflows. Support research efforts aimed at better understanding the protein sequence-to-function relationship Help partners measure where AI speeds up their design cycles, and where it doesn't. Drive product, engineering and research direction from field experience, e.g. benchmarks and evals for design and structure tasks (capabilities and safety). Scale your impact to the long tail of labs through reusable skills, cookbooks and docs. Be an ambassador for Claude in molecular design, from small settings to large conferences. You Might Be a Good Fit If You Have Hands-on experience applying protein or small-molecule design to real drug development programs, in an AI-first biotech, pharma, a rare-disease non-profit, a research institute, or a translational academic design lab. Experience with molecular dynamics (system prep, trajectory analysis) or large-scale antibody/immune-repertoire data, and with closing the loop against experimental results from a partner lab. Hands-on use of modern design and structure tools (e.g. AlphaFold, RFdiffusion, ProteinMPNN, Rosetta) to solve design problems, not only to build new models. Strong engineering skills: you can take an LLM-powered tool from prototype to production code, and write evals to measure its performance. Deep understanding on how to quantitatively measure success in drug design, experimentally and computationally. A scientist's instinct for understanding how AI can, and cannot, facilitate protein research and design Experience working directly with external customers or partners in a technical role. Clear written and verbal communication: docs partners can use without you, and talks that earn researchers' trust. A scrappy mentality: comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $280,000 — $320,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote-Friendly (Travel-Required) | San Francisco, CA | Seattle, WA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Legal Tech engineers play a specialized and critical role in keeping Claude at the frontier. Partnering closely with counsel, we provide custom infrastructure and guidance for complex, novel technical matters, empowering teams across the company to continue meeting our legal obligations as we innovate. As a Senior+ Software Engineer on our Legal Tech team, you'll build dedicated, highly secure, and reliable cloud environments and data processing and storage capabilities at speed and scale. You will own your scope end to end: from raw requirements all the way through to large-scale production systems that satisfy legal invariants and unlock new possibilities. The systems you build won't just be dependable and scalable; they'll be interpretable and auditable, demonstrating to skeptical audiences exactly how they worked and why results can be trusted. You'll be an essential member of a collaborative team, working together to solve difficult problems against fixed deadlines. You will own internal customer relationships as well: you'll gather, prioritize, and coordinate needs from colleagues on Privacy, Security, Research, and/or Infra as well as Legal, to ship the right capabilities on the right timelines. You'll act as a trusted advisor: clearly explaining technical concepts and constraints to inform legal decisions, and proactively designing new approaches to prevent classes of problems. Your infrastructure expertise will directly empower our business to calibrate and manage risk, innovating faster thanks to systems that build in legal considerations. Key responsibilities Build and operate dedicated cloud infrastructure, storage, and data pipelines for specialized workloads that can't run on general-purpose systems Design architectures with excellent security, privacy, reliability, scalability, and auditability baked in Partner with a wide range of internal customer teams to translate requirements into sound approaches and realistic ETAs Deliver against fixed deadlines Support complex and novel legal requests on controlled infrastructure, with verifiable chain of custody Pair with engineering teams across the company to extend existing infrastructure to support new workflows and/or legal requests Work with nontechnical stakeholders to clarify their needs through responsive, easy-to-follow dialogue Minimum qualifications Experience designing, building, and operating highly trusted infrastructure and data systems in production, including owning architectural decisions Experience working across large, complex, multi-team environments, including in stacks and code you don't own Ability to take ownership of a cloud account and secure it end to end (networking, storage, identity, encryption, least-privilege provisioning, etc.) on AWS and/or GCP Ability to translate legal and privacy requirements into sound technical designs and implementations that teams are excited to adopt A habit of verifying rather than assuming: designing checks for invariants and plainly naming what isn't proved Self-directed in a high-change environment, and comfortable resequencing quickly when new needs emerge Clear communication with nontechnical stakeholders, and an understanding of their needs Preferred qualifications Software engineering experience with an infrastructure, data, privacy, and/or security focus Proficiency with large-scale data tooling, such as distributed processing, lakehouse table formats, and/or query engines Understanding of data processing pipelines, LLM training, and/or provenance and lineage Experience with secure enclaves, confidential computing, clean rooms, or other purpose-built environments for sensitive data Background in eDiscovery, litigation support, or records retention at scale, including chain of custody and verifiable integrity The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.