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Location: New York City, NY; San Francisco, CA; 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 At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Claude is getting good at research. Given a well-posed problem, it can read the literature, write and run simulations, analyze results, and iterate on a design across physics, materials, chemistry, and engineering. But most of the hardest problems in science and engineering aren't well-posed. They live inside companies and labs with their own data, tools, constraints, and experts, and progress depends on turning all of that into work a model can actually do and check. Our Applied AI, Science & Engineering team takes Claude to the scientists and engineers working on hard problems in energy, materials, hardware design, and other physical-world fields. We build the tools  Claude needs to do real research and engineering work. Mostly that means software: the agent harnesses, integrations, evaluations, and working processes that turn a partner's problem into something Claude can make progress on and validate. We find real-world problems and test what we build through partner engagements, then feed our learnings back to our research and product teams. It's early, and the engineers who join now will shape how Claude gets applied to science and engineering. This is an engineering role first. You'll spend real time with domain experts, become the person who knows how to get Claude working in their field, and prototype quickly alongside them. Most of your time, though, goes into building and hardening the systems that make that work repeatable, not into writing recommendations or configuring someone else's product. A science or engineering background is a big plus, but what matters most is that you can earn the trust of expert researchers, turn a fuzzy problem into something concrete and checkable, and ship. Responsibilities Build the agent harnesses and research loops that let Claude carry a problem from literature review through hypothesis generation, simulation, analysis, and design iteration Connect scientific computing and simulation tools (finite element, CFD, electromagnetic, or molecular modeling codes, for example) so Claude can drive them reliably and at scale Design and build evaluations that tell us whether Claude's work is actually right, and be honest about where it isn't Sit with scientists and engineers at partner organizations to learn their problem, data, tools, and constraints, and turn open-ended questions into well-specified, verifiable tasks with clear success criteria Prototype with partners, ship pilots into their workflows, and cut anything that doesn't move the problem forward Turn what works in one engagement into shared tools, reusable components, and documented processes the next one can start from Be the technical voice on how Claude performs on science and engineering work, explaining results, limits, and tradeoffs clearly to researchers, engineering leads, and non-technical stakeholders alike Partner with our research and product teams to share where models fall short on science and engineering work, and help shape what comes next You may be a good fit if you Have 8+ years of experience building software, with strong engineering fundamentals and comfort across the stack, from data pipelines to tooling to quick interfaces Have built real systems with large language models, including agents, tool use, or evaluations Have worked on technical problems in a science or engineering field, such as physics, materials, chemistry, or electrical or mechanical engineering Have a track record of zero-to-one work in startup or startup-like environments\ Can work directly with expert users, understand their workflows deeply, and still keep the focus on building the right system rather than the one first requested Have good judgment about what can and can't be verified, and are comfortable saying a result isn't good enough yet Bring high agency, pick up new domains quickly, and hold strong opinions loosely Communicate clearly with researchers, engineers, and external partners, and care about the societal impacts of your work Strong candidates may also have An advanced degree or research experience in a physical science or engineering field Hands-on experience with scientific computing and simulation, numerical methods, or optimization Experience in industrial R&D, a national lab, or a deep-tech company in areas like energy, materials, manufacturing, or hardware Experience building alongside customers or technical partners, for example in forward-deployed, applied AI, or solutions engineering roles, ideally where you also owned the software that came out of it Experience with ML research, RL environments, or evaluation design Candidates need not have 100% of the skills listed above Formal certifications or education credentials Expertise in every scientific domain we work in Direct machine learning or AI research experience Deadline to apply: None. Applications will be reviewed 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: $405,000 — $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. 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 legal team operates at the frontier of some of the most consequential legal and regulatory questions of our time — from landmark copyright matters to first-of-their-kind AI regulatory frameworks emerging across dozens of jurisdictions simultaneously. As we scale, the volume and complexity of our discovery and information governance obligations are growing rapidly. We are looking for a Discovery Technical Operations Specialist to join our Litigation and Regulatory team and help build out Anthropic's discovery operations from the ground up, support active matters, and help drive information governance maturation. This is a unique opportunity to be a part of a critical function at one of the most closely watched companies in the world. You will work hand-in-hand with our discovery leads, litigation and regulatory counsel, outside counsel, discovery vendors, and cross-functional partners such as Security and IT to manage retention, preservation, collection, and production of electronically stored information (ESI) across active matters. Beyond matter-level support and programmatic development of discovery systems and processes, you will also help execute the development of Anthropic's broader information governance program, including data classification standards and defensible disposal practices that keep pace with a rapidly scaling AI company's evolving data landscape. The right person for this role will be equal parts technical operator and operational project manager. Key responsibilities Build and operate discovery operations across the full EDRM lifecycle (preservation, collection, processing, hosting, review, and production including for novel and AI-specific data types) Support the operational design and execution of the legal hold program including custodian identification workflows, hold issuance and tracking, periodic re-notification, custodian acknowledgments, and defensible release Support and improve the discovery technology stack including RelativityOne, in-place preservation and collection tooling across Slack, Google Workspace, and internal systems, and supporting analytics and review platforms including configuration, access controls, templates, and reusable workspaces Partner with discovery team, in-house counsel, outside counsel, vendors, and internal technical teams; coordinate matter execution, status, and escalations Partner with Security, IT, and product engineering to support Anthropic's data landscape, instrument new data sources for hold and collection, and ensure each ESI source has a governed retention, hold, and disposition path Improve and support the operational layer of Anthropic's information governance program: retention schedule execution, classification rollout, defensible disposition workflows, and data-inventory maintenance in close partnership with the Discovery Lead and information governance stakeholders Integrate AI and automation into the EDRM lifecycle: generative-AI-assisted review, advanced analytics, custom Relativity applications, and agentic workflow automation for intake, hold tracking, status reporting, and internal documentation Support active litigation, government investigations, and regulatory inquiries as the operational counterpart on the matter team coordinating workstreams, managing vendor execution, and surfacing operational risk and cost trade-offs to counsel Design and build internal tools to streamline and manage critical discovery workflows (legal holds, preservation, collection, ECA, and production), and develop dashboards that report on data management trends and cross-matter discovery status Minimum qualifications Hands-on discovery experience across the full EDRM lifecycle, with demonstrated ownership of operations on complex matters in an in-house legal department, government agency, law firm, or vendor A track record of supporting complex discovery operations functions Working knowledge of major discovery platforms (Anthropic uses RelativityOne), including administration, search and analytics, AI/TAR workflows, custom application development, and AI workflows Strong understanding of the Federal Rules on discovery and evidence, ESI preservation obligations, and proportionality, with the operational fluency to translate those obligations into workflows Experience operating discovery across modern enterprise data sources Slack, Google Workspace, mobile, and engineering systems and an understanding of how to bring novel data sources under preservation and collection Strong project management instincts and a track record of running multiple concurrent matters and programs under tight deadlines, with composure and precision Demonstrated ability to communicate technical discovery and operational concepts clearly to attorneys, executives, engineers, and non-technical stakeholders Preferred qualifications 6+ years of hands-on discovery experience across the full EDRM lifecycle Experience standing up discovery operations at a young and/or fast-scaling company, particularly in the context of new kinds of ESI Experience embedding with engineering or product teams to define discovery and information governance requirements, prioritize roadmap, and ship hold-capable and collection-capable features into core enterprise tools Hands-on integration of generative AI and agentic workflows (e.g., Claude, Claude Code, or similar) into operational discovery work project tracking, status reporting, internal documentation, custom tooling, and script maintenance Technical fluency working with engineering teams and modern infrastructure APIs, cloud (AWS, GCP), data pipelines, and version control and comfort writing, reading, or maintaining small scripts where useful Experience operating information governance programs at scale including retention scheduling, data classification, defensible disposition, and data mapping across heterogeneous enterprise data sources Experience with applying AI and automation to discovery operations, including generative AI for review, agentic automation, and operational tooling for hold tracking, reporting, and documentation A collaborative, hands-on orientation, with integrity and genuine curiosity about building operational programs in a fast-moving environment 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: $170,000 — $220,000 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. 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: Cyprus; Georgia; Poland; Spain; Serbia; Latvia We are looking for a Senior DevOps / Platform Engineer to develop and operate GoMining's cloud platform. The primary focus of this role is GCP and Kubernetes , infrastructure and application delivery automation, and the reliability and security of production services. You will maintain and improve our existing infrastructure, contribute to the development of the next generation of our platform, and help product teams ship changes safely and efficiently. Responsibilities Develop and operate infrastructure in GCP , including GKE, virtual machines, networking, load balancers, storage, and managed services. Manage Infrastructure as Code with Terraform : develop modules, manage state and dependencies, ensure reproducible changes, and identify configuration drift. Operate Kubernetes : upgrade clusters and platform components, configure autoscaling, workload placement, network policies, and resource allocation. Develop CI/CD and GitOps using GitLab CI and Flux / Argo CD, automating builds, checks, deployments, controlled releases, and rollbacks. Build observability across metrics, logs, distributed tracing, and actionable alerting. Define and improve SLIs/SLOs together with engineering teams. Troubleshoot production incidents and performance issues, conduct root cause analysis, and eliminate recurring failure patterns. Implement least-privilege access, environment and service isolation, secure secrets management and rotation, and infrastructure audit controls. Maintain backup processes and regularly validate recovery of critical data and infrastructure according to agreed RPO/RTO . Help engineering teams prepare services for production, including health checks, resource configuration, telemetry, and deployment procedures. Optimize cloud infrastructure usage and costs while maintaining reliability requirements. Maintain infrastructure documentation, operational runbooks, and recovery procedures. Requirements Strong hands-on experience independently operating production infrastructure and Kubernetes , including upgrades, troubleshooting, and disaster recovery. Strong experience with GCP , including GKE, Compute Engine, VPC, IAM, and Cloud Storage; good understanding of Cloud SQL, Cloud Logging, and Cloud Monitoring. Hands-on experience with Terraform , including modules, remote state, locking, importing existing resources, and safely applying infrastructure changes through CI. Deep knowledge of Kubernetes and containerization : Deployments, StatefulSets, Services, Ingress, storage, requests/limits, probes, autoscaling, RBAC, and NetworkPolicy. Experience with Helm and Kustomize . Strong Linux administration skills, preferably Debian/Ubuntu: processes, systemd, filesystems, disks, and resource troubleshooting. Strong networking fundamentals: TCP/IP, DNS, HTTP(S), TLS, routing, NAT, load balancing, and firewalls. Ability to troubleshoot connectivity issues across applications, Kubernetes clusters, networks, and cloud services. Experience building CI/CD pipelines, preferably with GitLab CI , and strong understanding of Git and GitOps principles. Understanding of runner permissions, secrets protection, and production deployment controls. Automation skills with Bash and Python , including maintainable infrastructure scripts and API integrations. Experience with monitoring, logging, and alerting using tools such as Prometheus, Grafana, or Cloud Monitoring . Practical experience operating PostgreSQL and understanding Redis and RabbitMQ, including availability, connections, replication or clustering, backup, and recovery. Strong understanding of cloud security principles: least privilege, service accounts, Workload Identity, secrets management, network segmentation, and access auditing. Ability to independently deliver infrastructure changes to a validated production result, explain technical trade-offs, and collaborate effectively with Engineering and Security teams. Nice to Have Experience with Flux CD, Argo CD, Ansible, and HashiCorp Vault . Experience with OpenTelemetry and distributed tracing. Experience migrating infrastructure between clouds or Kubernetes clusters, including database migrations with limited downtime. Experience designing disaster recovery strategies and conducting recovery exercises. Cloud cost optimization and capacity planning experience. Experience with DigitalOcean, Hetzner, or AWS . Ability to read and troubleshoot JavaScript / TypeScript applications. Experience operating financial or payment services with strict requirements around access control, auditing, reliability, and data integrity. Benefits Professional growth: support for courses, conferences, and English learning (up to 100% coverage). Work-life fit: remote or hybrid format with flexible hours across international teams. Paid leave: up to 20 vacation days +  8 company holidays + 5 personal days per year Recognition programs: structured performance reviews and team awards. Team culture: retreats in international locations (for example, company apartments in Cyprus).

Location: Sydney, Australia FP Markets Group of Companies is a well-established globally regulated Australian broker offering traders access to CFDs across Forex, Indices, Commodities, Stocks and Cryptocurrencies. We are growing and looking to recruit a Full-Time Customer Support Specialist in our Sydney office - a certified Great Place to Work® . The Customer Support Specialist plays a key role in delivering a smooth and professional client experience by assisting customers with their queries across phone, email and live chat, while guiding them on our products, website and trading platforms. The role is important in building client trust, resolving issues efficiently and ensuring customers receive the support they need throughout their trading journey. Reporting to: General Manager Responsibilities: Provide answers to customers by identifying problems and assisting with incoming queries by telephone, email and live chat Educating clients on how to use the Company’s website and trading platforms Communicating with clients regarding the company’s products and services via telephone, email and live chat Assisting other departments Candidate Profile: Computer literacy with excellent working knowledge of Microsoft Office applications Knowledge and experience in FX, CFD industry will be considered advantageous A team player with excellent communication skills Fluency in English is essential Knowledge of additional language will be an advantage but not essential Ability to work on public holidays Our offer: Welcoming, young and multicultural team with approachable leadership Ability to contribute to dynamic business at a growth phase High level of autonomy, support of ideas and putting your expertise into the best practices for the company Continuous personal development, training budget, growth with the company and opportunity to learn from industry leaders Competitive remuneration, regular salary reviews and performance-based incentive schemes Vibrant company life: from team activities to global celebrations Free access to multiple sports and wellness facilities across the country A day off on your Birthday Journey to FP Markets: Interview with People Function member (30 - 45 min) to assess match to our culture Interview with your future manager (45 min - 1 hour) to assess match to the job and the team and discuss role expectations Join our team and be a part of a professional, rapidly-growing company operating in a multicultural environment!

Location: Sydney, Australia FP Markets Group of Companies is a well-established globally regulated Australian broker offering traders access to CFDs across Forex, Indices, Commodities, Stocks and Cryptocurrencies. We are growing and looking to recruit a Full-Time Customer Support Specialist in our Sydney office - a certified Great Place to Work® . The Customer Support Specialist plays a key role in delivering a smooth and professional client experience by assisting customers with their queries across phone, email and live chat, while guiding them on our products, website and trading platforms. The role is important in building client trust, resolving issues efficiently and ensuring customers receive the support they need throughout their trading journey. Reporting to: General Manager Responsibilities: Provide answers to customers by identifying problems and assisting with incoming queries by telephone, email and live chat Educating clients on how to use the Company’s website and trading platforms Communicating with clients regarding the company’s products and services via telephone, email and live chat Assisting other departments Candidate Profile: Computer literacy with excellent working knowledge of Microsoft Office applications Knowledge and experience in FX, CFD industry will be considered advantageous A team player with excellent communication skills Fluency in English is essential Knowledge of additional language will be an advantage but not essential Ability to work on public holidays Our offer: Welcoming, young and multicultural team with approachable leadership Ability to contribute to dynamic business at a growth phase High level of autonomy, support of ideas and putting your expertise into the best practices for the company Continuous personal development, training budget, growth with the company and opportunity to learn from industry leaders Competitive remuneration, regular salary reviews and performance-based incentive schemes Vibrant company life: from team activities to global celebrations Free access to multiple sports and wellness facilities across the country A day off on your Birthday Journey to FP Markets: Interview with People Function member (30 - 45 min) to assess match to our culture Interview with your future manager (45 min - 1 hour) to assess match to the job and the team and discuss role expectations Join our team and be a part of a professional, rapidly-growing company operating in a multicultural environment!

Location: Warsaw, Poland Dentons Business Services EMEA is the operational backbone of Dentons, supporting the world's largest law firm in delivering exceptional service to clients across Europe, the Middle East, and Africa. As a crucial component of Dentons' global network, our EMEA business services team plays a key role in driving efficiency, innovation, and collaboration. About the Opportunity Dentons Business Services EMEA is currently looking for an Intern to support our Cash Collection Team. The role requires your full engagement and desire to learn new things. This is an excellent opportunity for you to see how the Finance department works in the law environment. Resposibilities Comply with the firm's policies, internal procedures Support in resolving client queries Support in ensuring inputs received from Partners are stored in the system Support in day-to-day and ad hoc tasks Support in the general projects and initiatives Working towards quality standards Support in generation of reports and data analyzing Working towards building professional relations Support in collaborating with Local Finance teams Following the work instructions Requirements Student status or fresh graduate (ideally with a focus on economics/finance) Willingness to work 2 days from the office Fluent command of Polish and English languages (written and spoken) Excellent written and verbal communication skills Computer literacy (MS Office, especially Excel, PowerPoint and Word) Autonomous and proactive working style Team player Availability min. 30hours/ week Benefits Language Capabilities We are a truly global law firm and as such, always welcome hearing from those with foreign language capabilities. Inclusion, Diversity & Equity Essential to our success as a global law firm is our ability to attract and retain the best talent from a diverse range of backgrounds. We want a work environment where everyone can reach their potential and we have an inclusive culture which respects individual differences. We undertake and support a number of internal and external initiatives aimed at increasing diversity within the profession and we encourage all our partners and staff to get involved. We welcome you to learn more about inclusion, diversity and equity at Dentons. Equal Opportunities Dentons is committed to providing equal opportunities for all. We welcome applications from candidates with disabilities and support those in the workplace who have a disability . Reward and Recognition Remuneration and benefits package will reflect the successful candidates experience and country where hired.

Location: Madrid, Spain; Barcelona, Spain; València, Spain Top 3 Reasons To Join Us Competitive Salary 100% Remote Working on the latest tech for the Insurtech Market Leader About Us At CoverGo, our mission is to empower all insurance companies to make insurance 100% digital and accessible to everyone. We are a leading global no-code insurance platform for health, life, and P&C We’re the winner of the Insurtech of the Year in all of Asia and other awards globally We work with insurance enterprise clients such as AXA, Bupa, MSIG, Dai-ichi, Bank of China Group Insurance, and many more We're an international, diverse team of over 120 people with 30 nationalities and team members working remotely from all over the world We are fully funded and backed by reputable VC funds and strategic institutional investors We have a global presence in Asia, EMEA and the Americas We’ve grown our annualized revenue by over 30x since January 2021 We’re constantly working towards making CoverGo a workplace that you love coming to. We deeply believe that bringing together a diversity of thoughts, expressions, and perspectives is key to building the best culture for equally diverse communities all over the world and a workplace that you love coming to. We deeply believe that bringing together a diversity of thoughts, expressions, and perspectives is key to building the best culture for equally diverse communities all over the world About the Role As a Digital Insurance Project Manager, your core responsibility will be to oversee and manage the implementation of new and/or existing projects within CoverGo's operations. This role presents an exciting opportunity for an individual with a strong drive to lead transformative projects in the insurtech industry. What You Will Do Engage and manage relationships with clients and stakeholders Lead project planning sessions with the internal team and client's staff Support solution proposals for client pursuits, proposals, and PoCs Participate in proposal and POC processes (i.e. design, submission, and review) Support the creation of contracts and related communication with clients Identify and help secure growth opportunities for existing clients Manage project progress and adapt work as required Ensure projects meet deadlines Manage relationships with clients and stakeholders Host regular/weekly project review and create reports with key metrics about team and project status using company standard metrics Oversee all incoming and outgoing project documentation Identify and manage issues, risks, assumptions, and dependencies Continuously optimize and improve processes and the overall approach where necessary What We Need Bachelor's degree in computer science or a related technical field is a plus Atleast 5 years experience as a Project Manager Atleast 3 years experience in insurance Insurance domain knowledge is a must Strong client facing experience is a must Technical skills are a plus Has experience seeing projects through the full life cycle Excellent analytical skills and problem-solving skills Strong interpersonal skills and extremely resourceful Proven ability to complete projects according to outlined scope, budget, and timeline Self-motivated and able to work independently Able, willing, and excited to work in a fast-paced collaborative startup environment Must be based in Spain Why You'll Love Working Here Fully Remote Paid Annual Leaves Annual Performance Bonus Remote Work Allowance Anniversary Bonus Health Insurance Company Activities and Events Learning and Development Plan CoverGo Company Video By submitting your application, you confirm that you have read, understood, and accepted the content of CoverGo’s Privacy Notice and you consent to the processing of your data as part of this application.

Location: Cyprus; Bulgaria; Poland; Russia; Dubai, United Arab Emirates; Georgia Job Description (JD) Job Title Head of Analytics – Global Multi-Product Broker Location Limassol, Cyprus (Hybrid) or Remote (UTC−1 to UTC+4) Reporting To Chief Marketing Officer (CMO) About the Role We are seeking an experienced Head of Analytics to establish and lead our analytics function from the ground up. This is a unique opportunity to define the company's data strategy, build the analytics architecture, and create the foundations for data-driven decision-making across a rapidly growing multi-product brokerage business. Operating across CFDs, cryptocurrency, proprietary trading, and prediction markets, the business has reached significant scale without a centralized analytics function. As the first Head of Analytics, you will have full ownership of building the data ecosystem, defining business metrics, implementing attribution models, and establishing analytics best practices that will shape the organization for years to come. Key Responsibilities Analytics Strategy & Leadership Build and lead the company's first centralized analytics function. Define the long-term analytics vision, roadmap, and operating model. Establish data governance standards, metric definitions, and reporting frameworks. Partner with executive leadership to enable data-driven strategic decisions. Direct and mentor embedded analysts across multiple business functions. Data Infrastructure & Architecture Design and implement the end-to-end analytics technology stack. Select and deploy data warehousing, transformation, visualization, and reporting solutions. Build scalable analytics infrastructure to support multiple financial products. Develop a canonical data model across the organization. Ensure data quality, consistency, accessibility, and governance. Marketing & Attribution Analytics Design and implement multi-touch attribution across: Paid Search Paid Social Affiliate Marketing Mobile Acquisition Partner Programs Build unified customer journey tracking from first interaction through trading activity. Deliver accurate ROI and customer acquisition insights across all marketing channels. Establish standardized marketing performance metrics. Business Intelligence & Performance Reporting Develop real-time executive dashboards and KPI reporting. Create a single source of truth for business-critical metrics. Build reporting frameworks across CFDs, Crypto, Prop Trading, and Prediction Markets. Translate complex analytical findings into actionable business recommendations. Experimentation & Decision Science Establish a company-wide hypothesis testing and experimentation framework. Design and evaluate A/B tests and controlled experiments. Ensure business decisions are supported by statistically sound analysis. Champion a culture of evidence-based decision making. Stakeholder Management Collaborate closely with Marketing, Product, Technology, Operations, and Commercial teams. Resolve cross-functional alignment on data definitions and reporting standards. Present analytical insights to senior leadership and executive stakeholders. Team Building Lead, coach, and develop embedded analysts. Design the future analytics team structure. Recruit and onboard analytics talent aligned with company culture and business goals. Key Deliverables (First 12 Months) Months 1–6 Build the analytics infrastructure and technology stack. Implement event tracking across all customer touchpoints. Deploy centralized data warehouse and transformation pipelines. Launch UUID-based attribution across all marketing channels. Establish data governance framework and documentation. Months 6–9 Develop and implement the organization's canonical data model. Standardize definitions for key business entities and KPIs. Align stakeholders around consistent business metrics. Months 9–12 Deliver real-time KPI dashboards across all business lines. Launch experimentation and hypothesis testing framework. Enable marketing and product teams to make data-driven decisions. Begin scaling the analytics organization through strategic hiring. Requirements Required Qualifications Bachelor's degree in Analytics, Data Science, Computer Science, Mathematics, Statistics, Economics, Engineering, or a related field. Master's degree is advantageous. Experience Required Significant experience in Analytics, Business Intelligence, or Data Leadership roles. Experience building an analytics function from the ground up. Strong background in financial services, brokerage, fintech, cryptocurrency, trading platforms, or similar digital businesses. Demonstrated experience implementing multi-touch attribution models. Proven success designing analytics architecture and selecting technology stacks. Experience leading cross-functional analytics initiatives. Experience managing or mentoring analytics professionals. Technical Skills Data Warehousing ETL/ELT Architecture SQL Python or R Business Intelligence tools (Power BI, Tableau, Looker, etc.) Marketing Attribution Platforms Event Tracking Frameworks Data Modeling Dashboard Development Statistical Analysis Experiment Design (A/B Testing) Data Governance Core Competencies Strategic Thinking Analytical Problem Solving Leadership & Team Development Stakeholder Management Business Acumen Communication & Influencing Skills Decision Making Change Management Project Ownership Innovation Mindset Success Profile The ideal candidate has: Built multi-touch attribution across paid, organic, and partner marketing channels. Designed analytics architecture from a greenfield environment. Experience within CFD, crypto, brokerage, fintech, or adjacent financial services. Successfully aligned stakeholders around standardized data definitions. Driven experimentation and evidence-based decision-making. Demonstrated confidence in challenging assumptions with data. A builder mindset who views the absence of existing infrastructure as an opportunity. Benefits Why Join Us Build the analytics function from the ground up with full ownership. Define the company's data architecture, governance, and reporting standards. Shape the future of analytics across multiple global trading products. Influence executive decision-making at the highest level. Build and lead a high-performing analytics team. Opportunity to make a lasting impact on a fast-growing global organization.

Location: New York City, NY; San Francisco, CA; 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. We are seeking an experienced Program Manager for a critical pillar of our Program Management function: Commercial Operations. This role will transform our commercial infrastructure into a revenue accelerator, building and executing the operational leverage that enables Anthropic to maintain velocity as we scale. You'll be responsible for managing and enhancing processes that support rapid product growth. The ideal candidate combines strategic thinking with operational excellence, someone who can both envision where we need to be in 12 months and build the infrastructure to get us there. Responsibilities Play a central role on the team that runs Anthropic's programs for Commercial Launches — helping evolve an established launch motion into a scalable, well-instrumented program that keeps pace with an accelerating product roadmap Run launches end-to-end through the Commercial launch process: lead intake and scoping for your portfolio of launches, translate each into its commercial-readiness requirements (pricing, billing, tax, marketplace, compliance and selling motions), and collaborate with product teams to develop paths to launch Identify where launches slow down today and drive resolution to prevent them from recurring: propose and implement process and system changes, clarify ownership, drive completion across partner teams like, Product, Engineering, Finance, Legal, and GTM. Build specific program components that don't exist yet — launch tiering, readiness criteria, playbooks, templates, SLAs; and develop training that shifts programs from late-stage gatekeeper to early-stage partner Take ownership of major program-improvement workstreams such as instrumentation (pipeline visibility, readiness scorecards, guides, throughput and cycle-time metrics) or workflow tooling and automation (intake, tracking, approvals, status) in partnership with Engineering and systems teams Work cross-functionally with Product, Engineering, Finance, and GTM teams to design clear interfaces and processes that span multiple teams You may be a good fit if you have Experience building and running new product introduction processes Experience building capabilities and solutions that enable launching in new ways, from pricing to geographies 10+ years of experience in operations, with demonstrated success in billing, payments, or commercial operations (high-volume SaaS experience a plus) Strong working knowledge of billing systems, subscription management, and payments platforms Proven track record of building and scaling operational programs in high-growth environments — taking things from 0-1 and then scaling beyond Willing to roll up your sleeves and do the operational work of building while also leading a team Experience with automation initiatives and partnering with engineering teams to build operational tooling Strong analytical abilities, problem-solving skills, and the ability to demonstrate ROI on operational programs Excellent cross-functional collaboration skills with the ability to influence stakeholders across GTM, Finance, Product, and Engineering Adaptability and comfort working in fast-paced, ambiguous environments where you need to balance multiple priorities simultaneously Excitement about building the operational backbone that enables Anthropic to stay on the exponential 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: $190,000 — $300,000 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. 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 Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. Sierra’s Applied Research team advances the quality, speed, and cost efficiency of the models powering our agents across a wide range of tasks. Our work spans post-training open-weight models for specialized capabilities and pioneering new approaches to voice AI, turning research breakthroughs into reliable production systems. WHAT YOU’LL DO - Tackle unsolved applied AI and ML problems. Pushing the boundaries of post-training, voice AI, and long-horizon task execution, building agents that can reason, adapt, and reliably carry out complex tasks for customers. - Determine when to build specialized models and when to use externally provided frontier intelligence, balancing quality, speed, and cost to deliver customer value. - Turn ambiguous product and customer problems into well-framed machine learning problems. - Develop, fine-tune, evaluate, and deploy models that improve Sierra’s customer-facing AI agents. - Advance our post-training work, from supervised fine-tuning toward reinforcement learning and long-horizon optimization. - Build rigorous evaluations that connect model performance to real-world agent quality. - Work with large-scale, proprietary datasets spanning text and audio interactions. - Collaborate across Sierra while taking ideas from experimentation through production deployment and customer impact. WHAT YOU’LL BRING - Strong experience building and deploying production machine learning and AI systems. We welcome backgrounds across applied ML, including search, ranking, recommendations, advertising, language, and speech. - Excellent judgment in framing product problems as ML tasks and selecting the simplest & most effective approach. - Experience working deeply with data, experimentation, evaluation, and model iteration. - A practical, evidence-driven approach to ML, with strong judgement around when a problem calls for modeling and when a simpler solution will deliver the best outcome. - The ability to operate with high agency and work across the stack when needed to deliver an outcome. - Alignment with Sierra’s values, including Craftsmanship, Customer Obsession, and Competitive Intensity. - A degree in computer science, machine learning, or a related field, or equivalent professional experience. EVEN BETTER… - Experience with supervised fine-tuning or reinforcement learning. - Experience in search, ranking, recommendations, or advertising systems. - Experience training and deploying language, speech, or multimodal models. - Experience designing model evaluations tied to real-world product outcomes. - Experience working with large-scale consumer datasets or high-volume ML products. - Contributions to applied ML research or benchmarks. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: San Francisco, CA Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. ABOUT THE ROLE Sierra’s AI agents depend on foundation models to reason and act in real time. The Inference team builds the systems that make those models fast, reliable, and efficient at scale. As a Software Engineer on Inference, you’ll help define Sierra’s inference architecture across both self-hosted models and third-party inference providers. You’ll work on the systems responsible for serving and routing inference, managing capacity and quota, and optimizing for latency, reliability, and cost. This is a systems-first role at the intersection of distributed infrastructure and AI. You don’t need to be an ML researcher—we’re looking for engineers who love complex systems problems and are excited to apply that expertise to one of the fastest-moving areas of AI infrastructure. WHAT YOU'LL DO - Partner with frontier labs and providers. At our scale, we rely on frontier labs, and inference providers to supply capacity, training and inference infrastructure. - Shape Sierra’s inference architecture. Design how inference traffic flows across models, infrastructure, and providers, including new serving and proxy layers as Sierra scales. - Build for low latency and high reliability. Develop systems for routing, failover, capacity management, and quota that keep inference performant and available across large-scale production workloads. - Build and operate self-hosted inference. Run models on GPU infrastructure, from building containers and operating inference engines to managing the underlying compute capacity. - Optimize inference performance. Work with the Applied Research team on techniques such as speculative decoding and serving-engine optimizations that improve latency, throughput, and cost. - Build across a hybrid inference stack. Work with both Sierra-managed infrastructure and leading inference platforms, making architectural decisions about where and how workloads should run. - Push the serving stack forward. Work closely with inference providers to tune engines and infrastructure for Sierra’s workloads. - Support the broader model lifecycle. Contribute to infrastructure that enables post-training while partnering closely with our Models and Agent Runtime teams. WHAT YOU'LL BRING - Deep systems thinking and strong distributed systems fundamentals. - Experience designing, building, and operating large-scale production systems. - Strong judgment around tradeoffs involving latency, reliability, capacity, and cost. - Experience taking ownership of complex infrastructure from architecture through production operation. - Excitement about applying systems expertise to AI infrastructure and learning quickly as the underlying technology evolves. EVEN BETTER - Experience with ML infrastructure, MLOps, or production inference systems. - Experience serving LLMs or other large models at scale. - Experience operating self-hosted inference and GPU infrastructure. - Familiarity with inference frameworks such as vLLM or SGLang. - Experience with post-training infrastructure or inference-performance optimization. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for distributed systems engineers and product-minded generalists to build the distributed runtime that powers large-scale LLM inference on Baseten. Our inference platform empowers customers to deploy and operate cutting-edge models with industry-leading performance, scalability, and reliability. It also powers Model APIs, our hosted endpoints for the latest open-source models. You'll work across the stack, from the developer experience customers use to deploy models, through the libraries behind features like tool calling and reasoning, down to the systems that orchestrate deployments on Kubernetes and route traffic efficiently. Your job is to make sure every model on our platform is fast, reliable, and cost-efficient. You'll join a small, high-impact team at the intersection of distributed systems, model performance, infrastructure, and product, helping define how developers use AI models at scale. This role is ideal for engineers who enjoy owning systems in production, solving hard integration problems, and making complex infrastructure simple and reliable for users.   EXAMPLE INITIATIVES You'll get to work on these types of projects on our Inference Platform: - The Baseten Inference Stack at NVIDIA Dynamo Day https://www.baseten.co/blog/nvidia-dynamo-day-baseten-inference-stack/ - 2x faster inference with KV cache-aware routing https://www.baseten.co/blog/how-baseten-achieved-2x-faster-inference-with-nvidia-dynamo/ - How Baseten multi-cloud capacity management (MCM) unifies deployments https://www.baseten.co/blog/how-baseten-multi-cloud-capacity-management-mcm-powers-cloud-self-hosted-and-hybr/#comparing-deployment-options-cloud-vs-self-hosted-vs-hybrid RESPONSIBILITIES - Build the infrastructure and orchestration systems that deploy and run large-scale distributed LLM inference, including routing, autoscaling, scheduling, and runtime management. - Design, build, and operate Model APIs, with a focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling, and multimodal serving. - Implement platform fundamentals such as API versioning, validation, usage metering, quotas, and authentication. - Instrument deep observability (metrics, traces, logs) and build repeatable benchmarks for speed, reliability, and quality. Help set best practices for testing, release automation, and operational excellence. - Debug and harden complex production systems spanning Kubernetes, distributed runtimes, networking, and GPU workloads to improve reliability and scalability. - Partner with Inference Performance engineers and other teams to make new optimizations broadly available to customers and easy to configure. - Own projects end to end, from architecture through deployment, monitoring, and iteration on customer feedback. Along the way, make thoughtful tradeoffs between performance, reliability, operational simplicity, and developer experience.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. in Computer Science, Engineering, or a related field, or equivalent practical experience. - 3+ years building and operating distributed systems, backend infrastructure, or large-scale APIs where reliability, latency, and scale are first-class concerns. - A proven track record of owning low-latency, reliable backend services, including rate limiting, auth, quotas, metering, and migrations. - Infrastructure instincts with a feel for performance: profiling, tracing, capacity planning, and SLO management. - Comfort debugging performance and reliability issues across multiple layers of the stack, from application behavior down to runtime and infrastructure internals. - A strong sense of developer experience. You think about how systems are used, not just how they work. - Eagerness to learn new languages, frameworks, and systems, and a real interest in inference engineering. Prior ML or LLM experience isn't required, though experience with model serving or inference systems is a plus. - Excellent written communication and collaboration skills, including writing clear design docs and working across functions.   NICE TO HAVE - Experience with or contributions to LLM inference engines and frameworks such as vLLM, SGLang, TensorRT-LLM, TGI, or Dynamo. - Deep Kubernetes experience, including operators and custom resources, plus familiarity with service meshes or API gateways. - Experience with distributed scheduling, autoscaling, or service orchestration. - Experience operating GPU workloads in production. - A background in developer-facing infrastructure or APIs, or contributions to open-source infrastructure or ML systems. - Familiarity with observability tooling, CI/CD systems, or release automation. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: San Francisco; Toronto; New York; Montreal; Seattle Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for inference performance engineers who want to make the world's most demanding AI workloads run faster and more efficiently. You'll work across the stack, from the inference engine and runtime through scheduling, serving, and routing. Along the way you'll apply techniques like prefill/decode disaggregation, speculative decoding, and KV-cache management. You'll reason from first principles about where time and memory go, find what's holding performance back, and close the gap. Your work directly impacts how fast our customers' models run and how efficiently we serve them. This role is ideal for someone who thrives in a fast-paced startup environment and is eager to make significant contributions to the exciting field of LLM inference.   EXAMPLE INITIATIVES You'll get to work on these types of projects as an Inference Performance engineer: - Agentic Kernels in Production https://www.baseten.co/blog/agentic-kernels-in-production/ - How we built the new fastest API for GLM-5.2 https://www.baseten.co/blog/how-we-built-the-new-fastest-api-for-glm-52/ - Live draft model training for speculative decoding https://www.baseten.co/blog/live-draft-model-training-for-speculative-decoding/#eliminating-traditional-bottlenecks - Making Kimi K3 Tokenization 18x faster https://www.baseten.co/blog/making-kimi-k3-tokenization-18x-faster-for-million-token-agentic-workloads/ - The Baseten Inference Stack https://www.baseten.co/resources/guide/the-baseten-inference-stack/ - Driving model performance optimization https://www.baseten.co/blog/driving-model-performance-optimization-2024-highlights/ RESPONSIBILITIES - Implement and productionize cutting-edge inference techniques, working deep in runtime internals. That includes quantization, speculative decoding, KV-cache reuse, chunked prefill, LoRA, guided generation for structured outputs, and custom scheduling and routing algorithms. - Profile and optimize inference end to end, from kernel launch overhead and memory layout up to request scheduling, prefill/decode disaggregation, and cache-aware routing. Run cross-layer investigations, such as tracing a tail-latency regression from request timing through routing and batching down to a kernel. - Turn performance into cost savings. Improve tokens per GPU-hour, raise utilization, and give customers and internal teams clear latency/throughput/cost tradeoffs. - Bring up and tune new model architectures on new hardware quickly, often in the same week they're released. - Build benchmarking frameworks that measure real-world performance across model architectures, batch sizes, sequence lengths, and hardware configurations. - Contribute upstream to open-source inference engines (vLLM, SGLang, TensorRT-LLM), and partner closely with model, infrastructure, and customer-facing teams to ship wins.   REQUIREMENTS - Bachelor's, Master's, or Ph.D. degree in Computer Science, Engineering, Mathematics, or related field. - Experience with one or more general-purpose programming languages, such as Python or C++. - Familiarity with LLM optimization techniques (e.g., quantization, speculative decoding, continuous batching). - Strong familiarity with ML libraries, especially PyTorch, TensorRT, or TensorRT-LLM. - Demonstrated interest and experience in LLMs. - Deep understanding of GPU architecture.   NICE TO HAVE - Proficiency in enhancing the performance of software systems, particularly in the context of large language models (LLMs) - Contributed to vLLM, SGLang, TensorRT-LLM, or another inference engine. - Worked on large-scale distributed serving: autoscaling, load balancing, multi-region or multi-cloud capacity. - Written or optimized GPU kernels (CUDA, Triton, CUTLASS, or similar) - Worked on quantization (FP8/FP4, AWQ, GPTQ) or speculative decoding in production. - Deep understanding of software engineering principles and a proven track record of developing and deploying AI/ML inference solutions. BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Location: Paris Workplace: OnSite ABOUT MISTRAL Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited. THE MISSION You will be the reference point for the most complex hardware interventions across our sites. Mistral's compute is our largest investment and the foundation of frontier AI in Europe. As a Senior Data Center Hardware Engineer, you own the interventions that require the highest level of technical expertise: multi-node failures in production, full-rack deployments of GPU-dense systems, and vendor escalations where you speak as the technical authority for our sites. You'll work end-to-end — compute, storage, interconnect, power and cooling interfaces — across our data center footprint, raising the bar on reliability as our capacity grows. This is a hands-on senior IC role: deep technical leadership and mentorship, no direct line management. Location: Based at one of our data centers in the Paris region, with occasional visits to our other sites as needed.   WHAT YOU'LL DO - Lead complex interventions — vendor-level and multi-node operations in production: full rack builds and bring-up, GPU-dense platform deployment (H100/H200-class and next-gen, including liquid-cooled racks), intricate recabling, post-restart diagnosis. You own the plan, the risk assessment, and the rollback. - Own vendor management — coordinate repairs, part replacements and escalations directly with hardware vendors; hold them to their SLAs; drive proactive fixes from failure trends. - Diagnose at depth — correlate symptoms across compute, storage, interconnect and cooling; read BMC/IPMI consoles, OS logs and crash dumps; methodical root-cause analysis that ends in concrete corrective actions. - Deploy and validate — structured bring-up and validation of new racks and platforms; work with networking and infrastructure teams to take installations from delivery to production-ready. - Lift the team — mentor and pair with L1–L3 engineers on live operations; turn your knowledge into SOPs, checklists and training material; propose and build small automation (Python/Bash) to shorten MTTR. - Work the facility interface — partner with critical facilities/engineering ops on power, cooling (air and liquid), PDU and monitoring (BMS/EPMS) boundaries; enforce ESD/LOTO/PPE and audit-ready change discipline everywhere. - Own spares & reliability — plan spares strategy, track fleet failure trends, and run proactive vendor actions before incidents happen.   ABOUT YOU - 6+ years in data center / server hardware or L2/L3 hardware support, including complex hands-on work in production environments (HPC/AI/cloud at scale strongly preferred). - End-to-end hardware expertise: CPU/memory/PCIe (incl. accelerators), NICs, PSUs, drives, network, power and cooling interfaces (DLC included); strong judgment on when and how to escalate. - Diagnostics depth: confident with BMC/IPMI logs, Linux logs and CLI checks; structured root-cause analysis. - Deployment experience: you've taken racks from delivery to production, with concrete examples to show for it. - Vendor fluency: you've managed hardware vendors — RMAs, field replacements, escalations — to concrete outcomes. - Impeccable safety and discipline: ESD/LOTO/PPE without exception; clean, labeled, auditable work. - Communication & mentoring: clear status updates and handovers; able to coach engineers during live incidents with composure. - Mobility: willing to visit our other sites in the Paris region as needed.   NICE TO HAVE - GPU-dense platform experience: NVIDIA H-series (H100/H200) or GB-series rack deployments. - High-speed interconnects (InfiniBand/RoCE), RAID/storage (NVMe/SAS/SATA), vendor tooling (iDRAC/iLO/IPMI). - Automation (Python/Bash) for ops tooling and reporting; ticketing (Jira/ServiceNow), inventory/RMA flows. - Hardware qualification, burn-in or factory validation background. WHAT WE OFFER We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link. PRIVACY POLICY Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

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 Frontier AI is on track to be among the most consequential and most adversarially-targeted technology in the world. The capability curve is steep, the adversaries who want these systems are extremely well-resourced, and the security bar this will eventually require is well beyond where the industry operates today. Incremental hardening alone is not going to close that gap, so we need breakthroughs and a group of people to go find them. Security Labs is that team. We run a portfolio of high-risk, high-expected-value security projects: the work that seems impractical until someone optimistic and stubborn enough actually tries it. Projects run on the order of weeks rather than quarters, and each one is either handed off to the Anthropic team that will own it in production or wound down with a writeup of what we learned. We expect a meaningful fraction of our bets not to land. This team is intentionally scrappy and ambitious. We're intentionally iterating fast on high-risk research bets and we expect a meaningful fraction not to land. If a 30% project success rate sounds uncomfortable, or uncharted and chaotic territory isn’t both frightening and exciting, this probably isn't the right fit. There are other places in Anthropic Security doing important work with more structure, less risk, and more certain paths to positive outcomes. The questions we're trying to answer include: Can our core research workflows survive extreme isolation? Can we replace trust with cryptographic guarantees? Can the models themselves become our most effective security control? What would it actually take to defend against a tier-1 state adversary, and how much of that can we build now? Who we're looking for. We're hiring generalists with rare depth. You're a strong software engineer as a baseline, and on top of that you've gone deep in at least one area most engineers don't get near: firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods, reverse engineering, or high-assurance and cross-domain systems. You've built things under your own direction, you're comfortable jumping layers when the problem demands it, and you'd rather take a swing at something that might not work than ship the safe incremental thing. You think the trajectory of AI matters a great deal, you're not comfortable with how the security side of it is going by default, and you'd rather be on the inside building the answer than watching from outside. Current Project Areas The portfolio changes as we learn. The kinds of bets currently in flight or queued: Standing up a prototype high-assurance research cluster: running real Anthropic training and research workloads under extreme isolation and physical security controls, and finding out exactly where productivity breaks and what we'd need to invent to get it back Provable inference: cryptographic verification (zero-knowledge proofs, attestation chains) that a given output came from a specific model running specific code, replacing "trust us" with math Build hypervisor-isolated microVM workload isolation across the fleet Compiling an ML kernel through a formally verified pipeline where every lowering step carries a machine-checked proof of equivalence, making compilation-layer sabotage mathematically detectable Regenerating clusters: automation that spins up a purpose-built cell, runs a workload, and tears the whole thing down on a TTL measured in hours, so attacker persistence has an expiry date Using Claude itself to drive security work end to end: threat modeling new compute platforms, rewriting critical services to zero external dependencies, running the test equipment that validates what hardware datasheets claim Part of your job is deciding what comes next. We hire people we trust to pick good bets, and project selection is owned by the engineers doing the work. Key responsibilities Own Security Labs projects end to end. You'll scope the bet, build the prototype, run it against real workloads, and bring it to either a hand-off or a documented exit Stand up novel security infrastructure fast (isolated clusters, attestation chains, hypervisor and runtime work, verification tooling) optimizing for what we learn rather than for permanence Find the receiving team early, bring them along while you build, and hand them something they actually want to own Work embedded with research and infrastructure teams (Pretraining, RL, Inference, Compute) to test whether their workflows survive what you're proposing, and document precisely where they don't Turn experimental results into short writeups that shape Anthropic's long-term security architecture, and into costed contingency plans we could execute on short notice Help pick the next round of bets and influence the industry to get better along the way Minimum qualifications Genuinely care about where AI is heading and want to work on the security problems that determine whether it goes well. This is the most important thing on this list Have real depth in at least one area most software engineers don't touch (e.g. firmware or hardware security, applied cryptography, OS / kernel / hypervisor internals, formal methods and verification, reverse engineering and exploit development, or high-assurance / cross-domain systems) Have built and shipped things under your own direction. Maybe you founded a company or research group, maintained an open-source project other people depend on, or shipped research that changed how people in your field work. We weight this far more than where you've worked or for how long Have a track record of choosing the problem yourself and seeing it through, rather than only executing a plan someone else handed you Are comfortable jumping between domains and layers of the stack when the problem calls for it, and have actually done so Have run prototypes or experiments where the goal was answering a hard question rather than shipping a permanent system, including ones that didn't pan out Write clearly enough to turn weeks of work into a couple of pages someone can act on Change your mind when the evidence says to, and are fine being the least-expert person in a room full of specialists Care about defense. Plenty of folks here come from offense and that background is valuable, but what you actually want to spend your time on now is making systems hold up Are a strong programmer (Python plus at least one of Rust, Go, or C/C++) and can stand up real infrastructure without that being the interesting part of your week Preferred qualifications Experience inside airgapped or high-side environments (classified networks, cross-domain solutions, ICS/SCADA, financial trading infrastructure) and the operational realities of working in them A background in offensive security, red teaming, or vulnerability research, with calibrated intuitions for which threats actually matter Familiarity with ML infrastructure (training pipelines, distributed schedulers, inference serving, accelerator hardware) sufficient for grounded conversations with researchers about what their workloads actually need A history of working in environments built around rapid iteration rather than rigid change control: startups, applied research groups, independent consulting, small security shops 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. 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: Boston, MA Workplace: OnSite At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. By combining advanced sensing, data science, and technology designed for continuous wear, WHOOP delivers insights that help members better understand and improve their health and performance. WHOOP is looking for a Senior Sensor Intelligence Engineer to join our Embedded Controls team within Sensor Intelligence and help shape the sensing capabilities across current and future WHOOP devices. Sitting at the intersection of signal processing, machine learning, embedded systems, and sensor technology, you will develop algorithms that interpret real-world sensor signals and intelligently control how sensors operate on-device. You will work across the sensing stack from understanding sensor physics and signal characteristics through algorithm development and embedded deployment to enable increasingly sophisticated sensing capabilities while meeting the power, compute, memory, and reliability constraints of a continuously worn device. RESPONSIBILITIES: - Develop signal-processing and machine-learning algorithms that interpret physiological, motion, and other wearable sensor signals, including applications such as activity and state detection, wear detection, signal-quality assessment, and device-state estimation - Design intelligent embedded control strategies that dynamically configure sensor behavior based on signal quality, device state, user context, system requirements, and power constraints - Characterize new and existing sensors by understanding signal behavior, noise sources, artifacts, dynamic range, sampling requirements, calibration, operating modes, and the impact of analog and acquisition architectures - Prototype algorithms and sensing strategies using tools such as Python or MATLAB, then partner with Firmware Engineering to translate them into robust, computationally efficient implementations suitable for resource-constrained embedded systems - Partner closely with Firmware, Electrical Engineering, Data Science, Hardware, and broader Sensor Intelligence teams to bring up new sensing modalities, debug issues across the sensing stack, and inform sensing architectures for future WHOOP products - Develop experiments, analysis frameworks, and validation methodologies to evaluate sensor and algorithm performance across users and real-world conditions, optimizing solutions for accuracy, robustness, latency, memory, compute, and power QUALIFICATIONS: - BS, MS, or PhD in Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Applied Physics, or a related technical field, or equivalent practical experience - Strong foundation in digital signal processing and time-series analysis, with experience applying techniques such as filtering, spectral analysis, sampling theory, noise reduction, and feature extraction to real-world sensor data - Experience developing signal-processing and/or machine-learning algorithms for noisy, artifact-prone sensor data and taking algorithms beyond offline analysis toward real-time, embedded, or production implementation - Strong proficiency in Python, MATLAB, or similar algorithm-development environments, with working knowledge of C/C++ and embedded-system considerations such as timing, memory, compute, and hardware interfaces - Working knowledge of sensor and electrical systems, including concepts such as ADCs, analog front ends, sampling, digital interfaces, noise, calibration, and signal acquisition - Ability to investigate and solve ambiguous engineering problems across algorithm, firmware, sensor, and electrical boundaries using strong experimental and analytical methods - Experience with wearable, physiological, optical, impedance, motion, multimodal, or related sensor systems is valued; experience with embedded inference, sensor fusion, fixed-point processing, quantization, low-power sensing, or microcontroller deployment is a plus - Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions. Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply. WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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 Secure Frameworks is the team in Anthropic's Security Engineering org that builds shared security libraries and frameworks the rest of the company builds on. We collaborate closely with teams and leaders across Anthropic to own critical security foundations, including workload identity and authorization, cryptographic frameworks, and the centralized access proxy that  secures traffic to internal applications. Our mission is to make the secure thing easy and the easy thing secure by helping Anthropic engineers get secure behaviour by default and preventing entire classes of vulnerabilities through careful design. We own what we ship, help customers adopt better security practices and at times we work embedded directly in research, infrastructure or product teams. About the role You will design, build and run security foundations used across Anthropic's fleet, from threat model through production, on-call and adoption. Much of the work is greenfield: our infrastructure is growing quickly and the timelines are compressed, so you will help define the architecture rather than inherit it. Depending on your strengths you will focus on one or two of the areas below and contribute across the rest. Build critical security foundations including cryptographic frameworks, mTLS infrastructure, secure serialization, and authorization systems, designed to prevent entire classes of vulnerabilities Partner with product, research, infrastructure, and other security teams to ensure frameworks integrate smoothly with lower-layer security controls Scope, design and build security services and libraries end-to-end, maintain them in production, and drive through ambiguous technical problems with minimal oversight Build and operate the zero-trust access gateway that fronts Anthropic's internal services Design and roll out authorization frameworks so services enforce least privilege consistently instead of each inventing its own access controls Own cryptographic frameworks and libraries Mentor engineers, contribute to hiring, and grow security engineering culture across Anthropic Minimum qualifications 8+ years of software engineering experience building security-relevant systems in production, including leading complex initiatives independently Strong programming skills in Go, Rust or Python Deep understanding of authentication and authorization systems: OAuth 2.0 / OIDC, JWTs, service-to-service auth, policy-based access control Hands-on experience with PKI, X.509, mTLS and workload identity Working knowledge of applied cryptography: choosing and composing primitives correctly, key management, and the ways libraries fail in practice Experience shipping and operating high-reliability services on Kubernetes across cloud and on-prem environments, including being on call for them A track record of bringing clarity and ownership to ambiguous technical problems and driving them to resolution across teams A strong sense of developer experience Clear communication across all levels of the organization Passion for AI safety and the role security engineering plays in building trustworthy AI systems Preferred qualifications Built security frameworks or libraries adopted across an engineering organization, and done the work to drive that adoption Built or operated a zero-trust / BeyondCorp-style access gateway or identity-aware proxy Migrated a fleet to mTLS at scale, including certificate issuance and staged enforcement Maintained or contributed to open-source cryptographic libraries Designed authorization systems using policy languages or relationship-based models Familiarity with ML infrastructure (training, inference serving) 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: $32,000 — $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. 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 The Security Risk team is responsible for how Anthropic identifies, prioritizes, and drives treatment of its most important security risks. We are rebuilding risk management to operate as an engineering function, using automation, quantitative risk and AI-native platforms to enable decision making. The risks we assess span Anthropic's full security landscape, so the team needs breadth across domains and the judgment to go deep wherever a decision demands it. Security Risk, in deep partnership with Security Engineering, helps define the security program and shapes how investment and treatment decisions get made. The conventional GRC playbook was not built for a company shipping frontier AI. You will help define what replaces it, with a direct line to CISO-level decisions. As a Security Risk Analyst you will take risk questions from leadership and partner teams and drive them to a decision. Sometimes that is a fast, structured qualitative assessment and other times it is a deep FAIR-based quantitative analysis. Either way you bring leadership a clear position, the tradeoffs, and honest uncertainty, and you defend it under challenge. In parallel, you will help turn quantitative risk into a product partner teams can leverage, and define the standards a growing risk function will run on. Key responsibilities Enable leadership and partner teams to make risk-informed decisions. Take ambiguous risk questions, drive them to a documented decision, and communicate the quantitative and qualitative tradeoffs clearly Lead quantitative analysis of the company's top security risk scenarios using FAIR, calibrated estimation, and simulation, working with the engineers who own the systems and presenting results in terms leadership can act on Partner with Security Engineering to assess threat scenarios and control effectiveness so security investment is right-sized to actual risk and remediation is sequenced where it buys down the most risk Frame escalations and risk treatment decisions with a clear recommendation, an honest statement of uncertainty, and re-evaluation triggers, and pressure test those decisions with risk owners Shape the analysis and narrative behind leadership risk reviews, and help define risk appetite and the risk metrics the organization should measure and why Use AI and automation to scale risk analysis, and own the calibration and quality review that keep the outputs trustworthy Turn one-off analyses into reusable methods, templates, and training so risk analysis becomes increasingly self service for partner teams, and raise the analytical quality of the risk register You may be a good fit if you Have owned security or technology risk analysis end to end, qualitative and quantitative, and can point to a decision your output changed, whether a funding call, a launch call, a remediation sequence, or a documented acceptance Have hands-on FAIR-style quantification experience, including scenario decomposition, calibrated estimation, and Monte Carlo simulation in Python, R, or spreadsheet tooling, briefed to decision makers Thrive in ambiguity. You frame a moving question into something analyzable, pick the depth that fits, and drive to a decision rather than a report Put defensible severity and likelihood on ambiguous problems, state uncertainty honestly, and change your position when the evidence changes Have enough technical security depth to decompose an attack path with security engineers and be credible in the room Can compress a complex risk position into one paragraph for the CISO, make the tradeoff explicit, and defend it under pointed questions Use Claude or other LLMs as daily working tools and review model output critically Are low ego and collaborative, build credibility through the work, and care about AI safety and the role security risk plays in it Strong candidates may also Have applied FAIR-CAM or another structured approach to control effectiveness and attack path modeling Have built or operated a cyber risk quantification program, or turned quantitative analysis into tooling, templates, or training that others ran Have helped define risk appetite or tolerance thresholds an organization actually used to make decisions Bring a background in security engineering, detection, threat intelligence, actuarial science, or decision science that grounds the numbers in real systems Are familiar with security risks specific to AI systems, such as goal or intent modification, and how they change traditional threat models 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. 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.