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Location: Virginia, United States Dexis is a dynamic professional services firm dedicated to partnering with government and community leaders both in the U.S. and internationally to achieve critical social outcomes in a rapidly changing world. At Dexis, you will experience a corporate culture of inclusiveness, respect, fairness, and trust. You will be given the means and mentorship needed to succeed, and your creativity will be rewarded. About the Position Dexis Professional Services (DPS) is seeking a motivated and enthusiastic Department of War (DoW) Capture and Business Development Specialist to support business development and capture activities across the opportunity lifecycle. This role is ideal for an individual with experience supporting DoW programs or customers who is interested in building a career in business development, capture management, and growth strategy. The Capture and Business Development Specialist will work closely with capture leads and business development professionals to help identify, qualify, shape, and advance priority opportunities. This role is ideal for a growth-oriented professional with experience supporting DoW customers, accounts, or programs who is looking to expand their responsibilities in business development and capture management. The successful candidate will combine an understanding of the defense market with strong relationship-building, analytical, and execution skills to help identify, shape, and advance strategic opportunities. This position offers significant opportunities for professional growth and increasing responsibility in customer engagement, opportunity management, capture strategy, and proposal development. Responsibilities Capture Management Own assigned capture workstreams and support Capture Leads across complex strategic pursuits, with increasing responsibility for customer engagement, opportunity strategy, competitive intelligence, teaming, and capture execution. Gather customer and market intelligence through research, customer engagements, industry events, and other sources to inform capture strategy. Build and maintain professional relationships with DoW stakeholders, industry partners, incumbents, and internal subject matter experts. Support and increasingly lead customer listening activities, including developing call plans, participating in customer engagements, documenting insights, and driving follow-up actions. Conduct opportunity assessments, competitive analysis, and research to inform teaming, staffing, and positioning strategies. Partner with recruiting to identify and engage Key Personnel and other priority candidates for strategic pursuits. Contribute to the development of win themes, value propositions, and capture documentation. Support proposal development activities, including content development, research, and coordination across teams. Maintain opportunity data, action trackers, and capture documentation to keep pursuits on schedule and ensure follow-through on capture actions. Business Development Monitor DoW priorities, procurement forecasts, industry trends, and customer activities. Identify emerging opportunities and help assess alignment with Dexis capabilities and growth objectives. Support customer outreach efforts and attend meetings, conferences, and industry events as appropriate. Contribute to internal knowledge management, lessons learned, and capture best practices. Collaborate effectively across business development, operations, recruiting, and proposal teams. Qualifications 5-8 years of professional experience supporting Department of War (DoW) customers, programs, or accounts. Experience supporting business development, capture, program management, or related growth-oriented functions within the federal market. Familiarity with DoW organizations, missions, priorities, and acquisition environments. Strong interpersonal skills and demonstrated ability to develop and maintain professional relationships with customers, partners, and internal stakeholders. Excellent written and verbal communication skills. Strong organizational and analytical skills with the ability to manage multiple priorities simultaneously. Self-starter with a proactive approach, intellectual curiosity, and a desire to grow into increasing capture and business development responsibility. Active DoD security clearance at the Secret level or ability to obtain and maintain one. Preferred Experience supporting technical DoW programs, Experience supporting federal capture efforts, proposal development, or opportunity shaping activities. Existing professional relationships within the Department of War community. Military service or experience supporting military customers. Experience using CRM and opportunity tracking tools. Experience supporting federal proposals, capture activities, or opportunity identification efforts. Below is the pay range aligned with this position. When developing a range, Dexis evaluates compensation holistically, triangulating between external market research , our budget for the position, and internal equity to arrive at a figure that is fair and competitive. Offers within this range will be based on an individual candidate's qualification, relevant education and experience, skills, performance, and organizational needs. Dexis pay range for this role: $80,000 — $95,000 USD Benefits Dexis offers benefits to support employees’ health, financial security, and well-being. The benefits outlined below are for full-time, US-based positions only. These benefits include: Medical and prescription drug coverage: A choice of three UnitedHealthcare medical plans, with coverage options for employees and eligible dependents. Dental insurance: Dental coverage for employees and eligible dependents, including preventive, basic, major, and orthodontic services, subject to plan limits. Company-paid vision insurance: Vision coverage for employees and eligible dependents, with premiums paid in full by Dexis. Employer-funded health reimbursement arrangement (HRA): Employees who enroll in the Silver HRA medical plan receive an employer-funded HRA to help pay eligible in-network deductible expenses. Company-paid life and disability insurance: Basic life and accidental death and dismemberment (AD&D) insurance, plus short-term and long-term disability coverage. Optional supplemental insurance: Voluntary supplemental life and AD&D insurance options, including life insurance options for eligible dependents. Employee Assistance Program (EAP): Company-paid access to confidential counseling and legal and financial support resources for employees and their families. Health and wellness resources: Virtual care, behavioral health resources, and wellness programs available through the medical plan. Benefits assistance: Personalized support with benefit enrollment, coverage questions, claims, and finding providers through the Employee Care Center. Participation, coverage, and employee contributions are subject to applicable benefit plan terms and eligibility requirements. Dexis is on a mission to help solve today’s most pressing global political, social, and economic challenges and create a world where all people are safe and prosperous. As a Dexis employee, you will be challenged, empowered, and mentored. Our motto is “find a way or make a way” — that’s how Dexis goes “all in.” How will you? If you are passionate about this opportunity, apply now! Only those applicants who meet the above criteria will be contacted for interview. Dexis is an Equal Opportunity Employer, and does not discriminate on the basis of race, color, sex, national origin, religion, pregnancy, disability, age, genetic information, military service, veteran status, ethnicity, citizenship, sexual orientation, gender identity, marital status, childbirth and related medical conditions, including lactation, or any other protected class under applicable law.

Location: UK, London Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We're hiring a Reinforcement Learning Engineer to join our Autonomy team based in London. In this role you will leverage reinforcement learning in both simulation and physical reality to build highly performant and robust manipulation policies. WHAT YOU'LL DO - Train language-vision conditioned manipulation policies via reinforcement learning (RL) in simulation and in the real world. - Construct challenging and diverse suites of manipulation tasks in simulation. - Partner with teleoperations to collect trajectories in simulation for behavior cloning. - Partner with testing and operations to establish real-world RL training pipelines. - Experiment with various ways of bringing policies trained in simulation to the real world. WHAT WE'RE LOOKING FOR - 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it. - Hands‑on with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference. - Experience solving real problems using reinforcement learning with deep neural networks in any domain. - Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code. - You are self-driven, pro-active, communicate efficiently, document experiments clearly and communicate trade‑offs crisply. NICE TO HAVE - Experience with simulators for robotics (Isaac Sim, MuJoCo etc.) - Experience in RL for robotics. - Experience building infrastructure for large-scale RL (e.g. using ray). - Publications at ICLR/ICML/NeurIPS or equivalent open‑source contributions. - Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks. WHAT WE OFFER - Competitive equity: stock options with meaningful upside as we scale. - 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown). - Private healthcare, including virtual and in-person care. - Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings. - Free daily breakfast, catered lunch, and snacks in-office. - Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics. - Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Location: Poland (Remote) About the Opportunity We are looking for a dedicated and proactive VIP Relationship Manager (VIP RM) to join our Poland team. As a VIP RM, you will play a key role in expanding our base of VIP clients with a focus on Poland. This role is focused on active traders, high-net-worth individuals (HNWIs), family offices, prop trading desks, and smaller corporate clients, driving our growth through partnerships and key client development in parallel to our institutional team, which, on the other hand, focuses on larger professional, enterprise and institutional clients. What You'll Be Doing Your primary goal will be to drive trading volume and maximize Assets Under Management (AUM) in the region through onboarding and retention of VIP clients. Revenue and Product Strategy Formulate a revenue strategy and optimization plan based on OKX's European product offerings Collaborate closely with the product team to gather client feedback, identify optimization opportunities, and enhance relevant product features Strategic Leadership and Partnerships Work closely with local executive leadership to contribute to the company's overall strategic direction Lead partnership efforts in Europe — identify suitable partners and execute negotiations to expand reach and revenue streams Client Management and Growth Manage relationships with HNWIs and key clients in Europe, ensuring positive customer experiences through proactive account management Build long-lasting client relationships to secure referrals and originate new prospects, working with operations to address roadblocks Compliance and Brand Advocacy Oversee legal and compliance aspects, including regulatory adherence, client KYC/AML processes, and reporting Serve as a brand ambassador, educating customers on OKX's full value proposition (trading tools to yield products), while escalating feedback to improve platform compliance and user experience What We Look For In You Core Qualifications Bachelor’s degree in Business, Marketing, Finance, or a related field (or equivalent professional experience in fintech/crypto). Fluency in English and Polish, with additional CEE languages (e.g., Russian, Ukrainian) considered a strong plus for regional client engagement. Industry Expertise 5+ years of proven experience in VIP business development and account management within crypto, fintech, trading, or wealth management, ideally in Poland or CEE. Track record of driving trading volume, AUM growth, and high-value client onboarding/retention in competitive markets like spot, margin, or derivatives trading. Technical and Analytical Skills Strong analytical skills to interpret market data, user behavior metrics, and performance dashboards for revenue optimization and product feedback loops. Deep familiarity with crypto products (e.g., perpetuals, staking, Earn, fiat integrations) and trading platforms. Soft Skills and Leadership Exceptional communication, negotiation, and relationship-building abilities, with experience managing VIPs such as HNWI, family offices, proptrading desks. Goal-oriented mindset with a history of exceeding KPIs in user acquisition, retention, and revenue targets through data-driven strategies. Compliance and Market Knowledge In-depth understanding of MiCA , MFSA , AML/KYC, EDD , and CEE financial regulations, including cross-border licensing and risk management. Proven ability to collaborate with legal, product, and ops teams to mitigate compliance risks while enhancing client experiences. Notice: All official OKX vacancies are published on this website. While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated. If in doubt, please apply directly through our official careers website. Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to OKX 's Candidate Privacy Notice .

Location: San Francisco Perplexity is seeking an Enterprise Product Growth Manager to own the full nurture and engagement engine for our enterprise and business buyers — from the first outbound touch through closed-won and into expansion. You will partner closely with Demand Generation, Sales, Product Marketing, and Revenue Operations to move accounts through every stage of the funnel, and you will build the AI-native tooling that makes those programs run. We are not looking for someone to operate yesterday's marketing stack. If you are the kind of marketer who writes their own SQL, prototypes their own agents, and treats every flow as something to automate rather than execute by hand — this role was written for you. RESPONSIBILITIES - Develop and own Perplexity's end-to-end enterprise lifecycle user states — outbound nurture, MQL-to-SQL conversion, opportunity acceleration, post-sale activation, expansion, and renewal — with direct accountability for pipeline created, pipeline progressed, and revenue retained. - Build and operate AI-native lifecycle tooling — agents that segment audiences from the warehouse, personalize copy at the account and persona level, choose channel and send time, QA before send, and read out results — replacing manual work in our stack wherever it appears. - Design and run multi-channel nurture across email, in-product, notifications, Slack, and emerging surfaces, tailored to enterprise personas with content tied to where each account sits in the funnel. - Partner with Demand Generation and Sales on top-of-funnel outbound: turn cold and intent-signaled accounts into engaged conversations, and instrument the handoffs that move them to opportunity. - Own post-sale lifecycle: admin onboarding, end-user activation, feature adoption, at-risk intervention, and expansion plays that grow seats and ARR inside existing accounts. - Run every program as an experiment. Define the hypothesis, the control, the primary metric, and the readout. Kill what doesn't work, double down on what does. WHAT WE'RE LOOKING FOR: - 7+ years in product growth, lifecycle, or growth marketing at a fast-paced startup, with a proven track record of moving activation, retention, and revenue metrics — including enterprise pipeline. - Experience owning growth end-to-end across the full user journey — from first touch and activation through expansion, monetization, and win-back. You've built growth loops and lifecycle programs that turn signups into engaged users and engaged users into revenue. - Deep understanding of audience segmentation. You think natively in personas, behavioral triggers, lifecycle stages, and product signals, and you know how to translate that into journeys, experiments, and in-product experiences that actually convert. - Great taste. You know how to craft copy and experiences that resonate across email, push, and in-product surfaces — for end users, admins, and executives alike — and you can tell the difference between a polished experience and a generic one at a glance. - Experience and deep interest in building homegrown AI-driven growth engines — programmatic personalization, agentic workflows, and rapid experimentation platforms to scale yourself. - Builder mentality toward tooling. You don't just operate the modern growth stack (Omni, HubSpot, Loops, Intercom, or equivalents) — you extend it. You've built your own internal tools, scripts, and automated systems to close gaps off-the-shelf software can't, and you'd rather automate a workflow than run it manually twice. - Comfortable with SQL. You can pull your own cohorts, validate your own segments, and read a dashboard without waiting on a data analyst. - Operates at high velocity. You ship daily, iterate weekly, and thrive in fast-paced, early-stage environments where processes are still being defined. Urgency is a default setting, not a mode you switch into.

Location: Argentina Remote Workplace: Remote ABOUT THE TEAM At Mural, we're changing how teams collaborate, think, and make decisions together. The Growth & Engagement team helps customers discover value through intuitive product experiences, rapid experimentation, and emerging AI capabilities that make collaboration more effective. We own key parts of the customer journey - from acquisition and onboarding to activation, engagement, retention, and monetization - and use data, experimentation, and customer insights to continuously improve those experiences. We're a cross-functional team of engineers, product managers, designers, and data partners who move quickly, measure outcomes, and learn from every experiment. We value curiosity, collaboration, and thoughtful technical craftsmanship, building systems that enable rapid iteration while maintaining a high bar for quality, reliability, and scalability.   YOUR MISSION  As a Senior Software Engineer on the Growth & Engagement team, you'll build the products, platforms, and experimentation capabilities that help customers discover value faster and achieve more with our product. You'll partner closely with Product, Design, Data, and other Engineering teams to identify opportunities, validate ideas through experimentation, and deliver experiences that improve customer outcomes and drive sustainable business growth. Beyond shipping features, you'll help shape the technical direction of the team, mentor other engineers, and establish engineering practices that enable us to experiment confidently and move quickly. WHAT YOU'LL DO - Design, build, and maintain customer-facing features that improve acquisition, activation, engagement, retention, and monetization. - Collaborate closely with Product, Design, Data, Marketing, and Customer Success to identify growth opportunities and translate customer feedback, product analytics, and experimentation to guide product decisions. - Design, implement, and analyze experiments using feature flags, A/B testing, and analytics to validate hypotheses and measure customer and business impact. - Build reliable instrumentation and event pipelines that help teams understand customer behavior and make informed product decisions. - Write high-quality, maintainable code while contributing to architecture, technical design, and long-term platform improvements. - Improve the performance, reliability, accessibility, and scalability of critical user journeys. - Mentor teammates through technical leadership, code reviews, design discussions, and knowledge sharing. - Contribute to roadmap planning, technical strategy, and continuous improvement of the team's engineering practices.  WHAT YOU'LL BRING -  5+ years of professional experience as a Software Engineer building and operating production software. - Strong proficiency building modern web applications. Experience with TypeScript, React, Node.js, and MongoDB or similar technologies, with the ability to become productive quickly. - Familiarity with Model Context Protocol (MCP) and the broader AI tooling ecosystem and the ability to quickly learn emerging AI technologies. - Experience leveraging AI-assisted development tools and workflows to improve engineering productivity, code quality, and delivery. - Experience building customer-facing products in close partnership with Product and Design teams. - A product mindset with the ability to balance customer needs, technical tradeoffs, and business goals. - Experience using analytics and data to inform engineering and product decisions. - Strong software engineering fundamentals, including system design, testing, observability, and operational excellence. - Excellent communication and collaboration skills, with the ability to influence technical decisions across cross-functional teams. - A track record of taking ownership of ambiguous problems, driving projects from concept to delivery, and mentoring other engineers. - Experience working on a Growth/Engagement team or in a product engineering role focused on experimentation and customer lifecycle improvements. - Experience working with business metrics such as activation, engagement, retention, conversion, and monetization to inform product and engineering decisions. - Experience designing, implementing, or analyzing product experiments (A/B testing, feature flagging, or similar experimentation frameworks). Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. EQUAL OPPORTUNITY  We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Location: Boston, MA Workplace: OnSite WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. Our Machine Learning Core Algorithms team is responsible for developing novel algorithms and features that expand our health and fitness capabilities with wearable sensor data. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. This role is located on our Core Algorithms team: performance-related insights for sleep, recovery, and exercise. As a Senior Machine Learning Engineer on our Core Algorithms team, you will design, build, and productionize ML systems that deliver meaningful, personalized metrics to millions of members. You will own the ML systems you build in collaboration with applied machine learning scientists. You will work at the intersection of data science, backend engineering, and cloud infrastructure – deploying robust, scalable, and reliable ML solutions built on physiological and behavioral data streams. This role emphasizes strong coding skills, system design, and the ability to deliver production-ready ML systems. Responsibilities: - Create, improve, and maintain production services that provide analysis for core features in collaboration with applied ML scientists and MLOps engineers. - Improve ML data pipelines, tooling, and validation systems that support robust model performance. - Work alongside applied ML scientists to translate research prototypes into production ML systems optimized for scale, latency and cost efficiency. - Collaborate with researchers and Product teams to align model development with physiological insights and member impact. - Build operational maturity within the Core Algorithms team as well as the broader Machine Learning team, developing processes for observability, alerting, and incident response (including on-call rotations). - Develop applied ML operational infrastructure (frameworks, evaluation criteria, performance validation). - Mentor other engineers and applied ML scientists on production practices, raising the bar through code and system design review. Qualifications: - Bachelor’s Degree in Computer Science, Data Science, Applied Mathematics, or a related field (Master’s preferred). - 4+ years of professional experience as an ML engineer, applied researcher, or software engineer with a focus on ML systems. - Experience working with time series data (wearable, physiological, or high-frequency sensor data). - Strong coding skills in Python with a track record of writing clean, production-quality code. - Experience designing, deploying and operating ML production systems at production scale (millions of users, real-time streaming and/or large-scale batch). - Experience deploying and maintaining ML backend services (APIs, reliability, observability, monitoring; AWS or GCP). - Preferred: 2+ years experience applying advanced mathematical and statistical techniques. This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.    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 https://www.e-verify.gov/ 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.   At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.   The U.S. base salary range for this full-time position is $150,000-$210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.    In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.   These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.   Learn more about WHOOP https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg.

Overview SOFTSWISS is looking for an Engagement Lead to manage the Content & Retention team and drive engagement, retention, and loyalty initiatives across multiple markets. Purpose of the role You will be responsible for developing engagement and retention strategies, optimizing the player journey, and delivering data-driven initiatives that improve player experience, retention, and long-term value. Key responsibilities Lead and develop a high-performing Content & Retention team. Define team priorities, processes, and ways of working. Own website content strategy and ensure quality across all markets. Drive retention initiatives, loyalty programs, and personalized player experiences. Build data-driven strategies to increase engagement, retention, and LTV. Lead segmentation, automation, and trigger-based communication programs. Foster a culture of testing, experimentation, and continuous improvement. Establish clear reporting and KPI tracking frameworks. Manage multiple priorities while maintaining high execution standards. Collaborate closely with Product, Technical Account Management, and Analytics teams to achieve business goals. Required Experience 3–5+ years of experience in retention, CRM, content strategy, or player engagement within iGaming, betting, gaming, or similar industries. 2+ years of leadership experience managing and developing teams. Proven track record of building successful content and retention strategies. Strong understanding of key metrics such as GGR, LTV, ARPU, retention, and churn. Experience with CRM platforms (Customer.io), marketing automation, segmentation, and loyalty programs. Data-driven mindset with hands-on experience in testing and performance optimization. Excellent project management and organizational skills. Strong leadership, communication, and stakeholder management abilities. Deep understanding of player behavior, engagement mechanics, and monetization strategies. Nice to have Russian-level knowledge. Main Advantages Private health insurance Sports benefits Comprehensive Mental Health Program Free English lessons (online) Local language courses Paid time off Maternity leave support Referral program rewards Upskilling, internal workshops, and participation in professional conferences and corporate events

Location: New York, New York, United States About the Role iCapital is looking for a Software Developer in Test to join the Quality Assurance team. The ideal candidate brings practical knowledge of agile development methodologies and engineering best practices. As a Software Developer in Test (SDET), this role will work closely with the Development and Testing team. This individual will serve as a hands-on test engineer with managerial experience, capable of understanding, enhancing, and implementing existing automation test frameworks. This role will also collaborate closely with other engineers and product managers to support feature‑based testing. Responsibilities Build and implement robust automated test suites. Integrate automated test suites with current build and deployment processes. Maintain automated tests to reflect updates in system design and architecture. Implement the automation framework with existing tools (JIRA). Create, Manage, and Utilize Defect workflows with automated test execution. Design and publish meaningful metrics to support automation test creation and Perform all types of testing such as functional, API, automation, performance and load. Qualifications 8+ years of experience with QA engineering delivery experience 4+ years of delivery within Agile SDLC teams ideally with CICD Programming experience in Java with focus on behavior driven development (BDD) and test-driven development (TDD) and design patterns, ideally within continuous integration (CICD) Experience with Java microservices and REST APIs and exposure to React front end Knowledge of Java, JavaScript, and SQL Proficient in CI/CD technologies such as Maven, Sonar, Git, TeamCity/Jenkins, and Docker AI Integration experience is preferred Exposure to banking or finance environments is preferred Prior experience testing ETL processes is preferred Hands-on experience with testing tools including JUnit, RestAssured, Playwright, Protractor, and JMeter Benefits The base salary range for this role is $120,000 to $160,000. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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 Anthropic manages one of the industry's largest AI fleets — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute. As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around Capacity. You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment. This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need. Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other. Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number. Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO. Key responsibilities Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs. Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. Directly influence decisions around a significant area of company investment. Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline. Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration. Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is actually usable. Treat the output as a product, not a pipeline. Gather your own requirements, define schema contracts, and design for consumers ranging from research engineers to a CFO — including on-call and SLOs, because these surfaces are load-bearing for the company. What you bring A strong track record building and operating production systems. This is a hands-on engineering role with a devops flavor. Python and SQL at production quality. Most pipeline code is Python; the presentation layer is BigQuery SQL, including table-valued functions and views. Both need to be idiomatic, well-tested, and maintainable. Deep experience with at least one major cloud provider (Amazon Web Services, Google Cloud, or Microsoft Azure) and its operations Experience with observability tooling stack, including Prometheus, PromQL, and Grafana, including writing recording rules and building monitoring that engineering teams rely on. Ability to gather your own requirements and work across organizational boundaries in an ambiguous environment with limited direction. Preferred qualifications Experience with capacity planning, resource management, or cost attribution systems at a hyperscaler or in a large-scale machine learning environment. Time spent in product engineering and developer experience absolutely counts here. Scheduling and packing efficiency experience, or profiling-driven optimization of large distributed workloads. Multi-cloud data ingestion experience, especially normalizing billing exports, reservation APIs, on-demand capacity reservations, commitments, and vendor telemetry from providers with different billing arrangements. Total cost of ownership and forecasting experience, including decomposing whether infrastructure growth is causal or correlated with business drivers. Accelerator infrastructure familiarity. GPU metrics (DCGM), TPU utilization, Trainium power and utilization metrics, or experience with machine learning training and inference systems at the hardware level. Experience building internal data products with self-service access, schema contracts, API serving, documentation, and discoverability. Not just pipelines, but thinking about how the data gets consumed. Storage efficiency, retention, and lifecycle program experience at very large scale. 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: United States - Remote; Chicago, IL; Texas - Remote; Boston, MA; Florida - Remote; Minneapolis, MN; Michigan - Remote; Canada - Remote Workplace: remote About the Role The Azul Sales Engineer is a hands-on, deeply technical pre-sales leader responsible for delivering the technical win across opportunities within their territory. Azul sells to the most demanding Java estates in the world — enterprises running mission-critical, high-throughput, latency-sensitive applications on the JVM — so this role demands genuine engineering depth, not just presentation polish. A Sales Engineer earns credibility with engineers, architects, and executives alike by getting hands on: running technical evaluations in the customer’s own environment, tuning the JVM, interpreting GC and performance data, and translating measurable technical outcomes into clear business value. Beyond individual deals, the Sales Engineer uses their experience to mentor and uplevel the broader SE team. What You'll Do (aka Responsibilities) Own the technical win. Drive pre-sales engagements end to end — discovery of the prospect’s business and technical challenges, mapping Azul portfolio capabilities to those challenges, and validating the solution through demonstration and hands-on proof. Lead hands-on pilots. Design, scope, and personally execute product pilots and proofs-of-concept inside the customer’s existing environment: installing and configuring the JVM, running representative workloads, and capturing empirical results the customer trusts. Prove performance. Plan and run performance-focused engagements: establish benchmarks and success criteria, measure latency, throughput, GC pause behavior and resource efficiency, analyze GC and JIT logs, tune JVM settings, and quantify the improvement Azul delivers against the incumbent. Win at enterprise scale. Navigate complex, multi-stakeholder enterprise engagements (large production estates, strict SLAs, security and compliance review, and long procurement cycles) coordinating technical validation across many teams and environments. Present at every altitude. Deliver presentations and demos across all technical levels, from CxOs to hands-on developers, to “make the complex simple” and communicate Azul’s value to each audience. Respond to technical requirements. Understand and respond to solicited and unsolicited proposals (RFI/RFP) by aligning Azul capabilities against detailed technical and business requirements. Orchestrate the extended team. Engage Product Management, Engineering, and the CTO office as needed to remove technical blockers and secure the win. Partner on territory strategy. Work alongside your Account Executive(s) on territory planning: pipeline generation, growing existing accounts, and enabling partners. Grow and retain customers. Nurture existing clients to promote customer success and to create new upsell and cross-sell opportunities. Evangelize. Present at conferences, workshops, and roadshows to raise awareness of the Azul portfolio and build funnel. Mentor the team. Provide expert assistance to other SEs on pilot planning and execution, run training sessions, and serve as a primary mentor to onboarding SEs. Be a trusted advisor. Advise your manager on product, territory, and team matters. Technical Competencies These are the core technical strengths that define a successful Sales Engineer at Azul: Java & the JVM. Deep, hands-on knowledge of Java internals and the JVM: class loading, JIT compilation, memory model, and garbage collection. Able to read and reason about GC logs and runtime behavior, not just describe them. Performance engineering. Practical experience benchmarking, profiling, and tuning JVM-based applications for latency, throughput, and scale; comfortable diagnosing GC pauses, warm-up, jitter, and resource-efficiency issues in production-like conditions. Hands-on aptitude. Confident on the command line and in customer environments: installing, configuring, and troubleshooting runtimes; able to build and run a POC independently. Enterprise application stacks. Solid understanding of Java-based applications and frameworks that run on or alongside Azul products (e.g., Cassandra, Kafka, Solr, Spring). Cloud & containers. Working knowledge of cloud platforms (e.g., AWS, Azure, GCP) and container/orchestration technologies (e.g., Docker, Kubernetes). Portfolio SME. Demonstrate SME-level depth and breadth across the entire Azul product suite, and continuously grow technical acumen through enablement, hands-on experimentation, and self-study. What You'll Bring Qualifications 5+ years in a Sales Engineering / pre-sales role supporting enterprise software, ideally in the Java, middleware, performance, or infrastructure space. 3+ years of hands-on Java development or testing experience with a demonstrable command of Java architecture. Proven track record of hands-on pilots and POCs and of performance-related engagements where you measured and demonstrated technical results in a customer environment. Experience selling into large enterprises — complex, multi-stakeholder, mission-critical production environments. Bachelor’s degree (or equivalent) in Software Engineering, Computer Science, or a related IT discipline; a master’s or higher in an IT or business discipline is a plus. Working knowledge of cloud and container technologies (e.g., AWS, Docker/Kubernetes). Solid knowledge of sales process and CRM (MEDDICC and Salesforce preferred). Willing and able to travel up to 30%. Fluent in your territory’s primary language, with strong professional English. Skills & Attributes Strong oral and written communication, effective one-on-one and in front of large groups. Proven critical-thinking and problem-solving skills; able to solve complex technical challenges with minimal supervision. Highly organized, detail-oriented, with excellent time management. Highly professional and ethical. Thrives in a fast-paced environment and can multitask across client challenges, meetings, and team needs, occasionally outside normal business hours. Collaborates across disciplines, with the EQ to understand multiple perspectives toward a common goal. A proven winning record. #LI-MD1 What we Offer ·         Comprehensive compensation and healthcare packages ·         Referral Program ·         Work-life balance, remote-first, paid time off, company shutdown, holidays ·         Work with top experts worldwide whom contribute to the Java ecosystem   Our Culture & Values   ·         Maniacal Customer Focus ·         Innovation & Excellence ·         Initiative & Courage ·         Impact & Influence ·         Integrity & Transparency ·         Diversity, Inclusion & Teamwork   Azul participates in E-Verify. As a US employer, Azul Systems, Inc. uses E-Verify to confirm the employment eligibility of all newly hired employees working in the United States. For more information about E-Verify, please visit www.e-verify.gov.   Employment at Azul is contingent upon the completion of reference and background checks. We offer a comprehensive compensation and benefits package where you’ll be rewarded based on your performance and recognized for the value you bring to the business. The base salary range for this job $150,000-$175,000.  This job is also eligible for commission/variable pay.  Individual base salaries are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography. In addition, our benefit package includes medical and dental coverage, equity participation plan, 401(k) plan, and a wide range of paid time off options.

Location: San Francisco, CA | New York City, NY | Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the account abuse team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be account compromise: Anthropic's enforcement systems have to distinguish customers whose accounts have been compromised from actors abusing the platform — and today those two populations can look identical in the data. Stolen credentials and leaked keys are a growing abuse vector, and the collateral damage from enforcement against them lands on legitimate users. You'll own this problem end to end: detection, revocation, user notification, remediation, and the criteria for restoring access — turning what is today ad hoc incident response into a scalable, repeatable program. This position may expand into broader areas of enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Key responsibilities Investigate credential-compromise incidents across first-party and third-party platforms, tracing actor behavior across accounts and surfaces Design and operate remediation workflows for compromised accounts: revocation, customer notification, and standards for restoring access Partner with Engineering and Data Science teams to improve how we separate compromised-customer traffic from willful abuse Enforce usage policies with a focus on detecting and mitigating potentially harmful use of AI systems Work with threat intelligence on emerging credential-abuse patterns and the actors behind them Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Write the policy framework for compromise scenarios, including cases where Anthropic can't independently verify a customer's security posture Act as the enforcement SME when account compromise intersects with active abuse investigations Minimum qualifications Experience in trust and safety, fraud investigation, security operations, or a related field Subject matter expertise in one or more of: account takeover, credential abuse, session security, or incident response Experience designing or operating enforcement, remediation, or customer-recovery flows — not just detection Comfort using data (SQL or similar tools) to trace actor behavior across accounts and to measure what's working A thoughtful perspective on the tension between protecting the platform and restoring access for legitimate compromised customers Strong written communication skills, with experience producing clear briefs about messy incidents for technical and non-technical stakeholders Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams Preferred qualifications Familiarity with credential-theft ecosystems or threat intelligence tooling Experience working with fraud/risk vendors (e.g., device or network intelligence platforms) Experience with API platform abuse specifically, not just consumer-account ATO A deep interest in AI safety and responsible technology development Experience writing effective prompts for generative AI systems in a content review or enforcement context 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: $245,000 — $285,000 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: Yerevan, Armenia Description We are looking for a data-driven Business Data Analyst to join our Partner Performance Analytics Team. This role is focused on analyzing partner business performance, evaluating bonus campaign effectiveness, identifying growth opportunities and business risks, and providing actionable recommendations that drive partner success and company profitability. The ideal candidate combines strong analytical capabilities with business thinking and has experience working with performance metrics, commercial analysis, and data-driven decision-making. Experience within iGaming, online betting, casino, or retention analytics environments is highly preferred. Responsibilities Analyze partner performance across key business metrics and identify growth opportunities and performance gaps Monitor and evaluate the effectiveness of bonus campaigns, promotional activities, and retention initiatives Assess the impact of bonuses and promotional costs on revenue, profitability, retention, and player behavior Identify trends, anomalies, risks, and underperforming business areas through data analysis Prepare actionable recommendations to improve partner performance and business outcomes Translate complex data into clear business insights and recommendations Requirements 2+ years of experience in Business Analytics, Business Intelligence, Commercial Analytics, Performance Analytics, or a similar role Strong analytical and problem-solving skills Advanced SQL knowledge Experience with Power BI or similar tools Experience working with large datasets and performance reporting Ability to identify business drivers behind data trends Upper-Intermediate or higher English level Experience in iGaming, Sportsbook, Casino, Affiliate, CRM, Retention, or Loyalty Analytics Understanding of key iGaming metrics such as GGR, NGR, Retention, Bonus Cost, Conversion, Churn, ARPU, and LTV Experience analyzing promotional and bonus campaign performance Familiarity with A/B testing and performance optimization methodologies Knowledge of Python is a plus Ability to transform data into actionable recommendations Strong attention to detail Ability to work independently in a fast-paced environment Focus on business impact rather than reporting only

Location: New York City, NY; San Francisco, CA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Safeguards team is responsible for ensuring our models and products are developed and deployed safely. We're looking for engineers for our Review Tooling team, which builds the systems that humans — and increasingly Claude — use to investigate potential harms and take enforcement actions across Anthropic's first-party products and third-party cloud platforms. You'll own the tools our safety investigators rely on to understand what's happening on our platforms and act on it, as well as the platform underneath those tools. That platform includes data analysis capabilities, privacy-preserving primitives that keep review workflows compatible with our data retention commitments, and a sandbox environment where new review interfaces and workflows can be built and iterated quickly. These are internal tools, but they are anything but low-stakes: the speed, clarity, and reliability of this tooling directly determines how quickly Anthropic can identify harmful behavior, make sound enforcement decisions, and feed signals back into model training and safety classifiers. You'll partner closely with policy, operations, data science, legal, and privacy teams to ensure our enforcement systems are effective, accurate, and trustworthy. Key responsibilities Build investigation, review, and enforcement tooling for both first-party and third-party platform surfaces — including case queues, investigation views, decision and audit logging, and account-actioning workflows Develop the platform layer of reusable APIs, data storage, and backend services that lets new review workflows be stood up quickly and safely Stand up and run deployments of this tooling across multiple clouds, including inside cloud-provider partner environments where data must stay in place. Keep the deployments consistent through shared deployment pipelines, smoke tests, observability, and alerting Scale review through automation, including enabling reviewers to use Claude effectively and building toward Claude-assisted and Claude-driven review workflows Partner with policy, operations, legal, privacy, and data science stakeholders to translate enforcement and investigation needs into reliable, well-designed systems that measurably reduce handling time and decision error Instrument the tools you ship — surfacing metrics on queue health, reviewer throughput, and decision quality — and ensure tooling evolves alongside new privacy primitives and data retention commitments Minimum qualifications A technical background in full-stack or platform engineering, with the ability to engage deeply in architecture and design discussions Experience shipping internal tools or platforms with demanding operational users, and a track record of improving their workflows measurably Experience working cross-functionally with non-engineering partners such as operations, policy, or legal teams Excellent communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders Care about the societal impacts of AI and want your work to make powerful systems safer Preferred qualifications 8+ years of industry software engineering experience Experience building data labeling, trust and safety, integrity, fraud, or abuse-prevention tooling, or other systems supporting human review at scale Have built systems that handle sensitive or regulated data, with requirements around access control, auditability, retention, and data residency Have worked across multiple cloud providers, or built infrastructure designed to be provider-agnostic A product-minded approach to internal users: you work directly with the people using your tools, watch where they struggle, and fix it 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: United States (Remote) Grafana Labs is the company behind Grafana Cloud, the fully managed observability platform trusted by more than 10,000 organizations to ensure reliability, resolve incidents faster, and optimize telemetry at scale. Built on open source and open standards and designed for interoperability across any stack, Grafana Cloud brings AI to observability and observability to AI, giving teams (and their agents) unified visibility so they can see, understand, and act on all their disparate data, wherever it lives, and move at the speed of their ambitions. Customers, including Anthropic, Bloomberg, NVIDIA, Microsoft, and Salesforce, rely on Grafana Labs. We are a 100% remote company with team members across 40+ countries, backed by leading investors including Lightspeed Venture Partners, Sequoia Capital, GIC, Coatue, J.P. Morgan, CapitalG, and Lead Edge Capital. Learn more at grafana.com and follow us on LinkedIn and X . We’re scaling fast and staying true to what makes us different: an open-source legacy, a global collaborative culture, and a passion for meaningful work. Our team thrives in an innovation-driven environment where transparency, autonomy, and trust fuel everything we do. You may not meet every requirement, and that’s okay. If this role excites you, we’d love you to raise your hand for what could be a truly career-defining opportunity. This is a remote opportunity and we are looking for candidates from the U.S. or Canada. Residents of Quebec are not eligible for this role. At Grafana Labs, we build observability tools that help users understand, respond to, and improve their systems – regardless of scale, complexity, or tech stack. We recently started a skunkworks initiative with a mission to bring observability to the rest of the business. Our goal is to make Grafana the single best place where humans and AI agents understand and act on real-time data from across the enterprise. As part of this initiative, we are building an AI-native data intelligence system that gives agents reliable, governed access to enterprise context. This system helps agents retrieve the right data, metadata, definitions, lineage, quality signals, and institutional knowledge without every agent builder having to maintain their own brittle context files. The principle is simple: the context system retrieves, agents decide, and data teams maintain the intelligence. The new team is a mix of seasoned Grafanistas and new hires. We operate with a high degree of autonomy and ownership, both as individuals and as a team. Engineers are empowered to make decisions, move quickly, and validate ideas early – while being supported by a deeply collaborative culture that values curiosity, feedback, and cross-functional partnership. We’re looking for a Senior-level Backend Engineer to help build the first production services for this context layer management system. You will design and ship the core backend architecture that powers ingestion, context storage, retrieval APIs, and agent-facing integrations. This is an early-stage role on a high-autonomy team, so you should be comfortable working through ambiguity, making pragmatic architectural decisions, and building systems that can evolve from internal dogfooding to production-grade SaaS. As the team matures, there’s a broad opportunity to expand or redefine this role based on impact and initiative. Key responsibilities: Build the core backend services: Design, implement, test, and operate the first services for context ingestion, context indexing, retrieval orchestration, API access, source configuration, and system administration. Create a scalable SaaS foundation: Help define and build the architecture for a multi-tenant service, including tenant isolation, usage tracking, quotas, audit logs, background jobs, and reliable service boundaries. Power agent-facing retrieval workflows: Build APIs and service interfaces that allow AI agents, MCP tools, CLIs, and internal applications to retrieve relevant context, provenance, confidence signals, and warnings. Work across product and infrastructure: Partner with the team to make practical tradeoffs between fast experimentation and long-term reliability, especially as the project moves from prototype to production. Operate what you build: Instrument services with metrics, logs, traces, alerts, and dashboards. Use observability tools to understand system behavior and improve reliability. Contribute to technical direction: Help shape the architecture, service boundaries, storage choices, API contracts, deployment patterns, and engineering practices for a new product area. Effective communication: You’ll be working in a highly dynamic and collaborative environment, so we need someone who can communicate effectively and contribute across teams. Ownership and impact: Take full ownership of the AI solutions you develop, ensuring they are not only innovative but also scalable, maintainable, and aligned with real user workflows. What we're looking for: Strong engineering skills: Solid experience building production-grade, user-facing software systems. You’re a self-starter, capable of tackling complex engineering problems and making UI design decisions with minimal supervision. AI experience with a practical mindset: You’re familiar with AI technologies and frameworks, and you focus on delivering high-quality solutions that work in the real world, not just in theory. Quick iteration and experimentation: You’re comfortable releasing prototypes, collecting feedback, and iterating with a pragmatic mindset. Proven initiative: You take ownership and drive projects forward, pushing boundaries to find the most impactful solutions. You can deal with ambiguity and are able to define scope where things are loosely defined. Collaborative attitude: You communicate effectively with your peers. You’re open to feedback, and you bring a solutions-oriented mindset to the table. Requirements: Experience with LLMs, prompt engineering, and building applications powered by GenAI. Proven track record of delivering software that made it into production and is actively used by users. Exposure to working in cloud-native environments (e.g., AWS, GCP, Azure). Experience using observability tools to understand and troubleshoot system behavior. Nice to have: Experience building or working with agent frameworks or multi‑agent workflows. Experience as a data analyst or work with data platforms (e.g., Looker, Tableau, PowerBI, Snowflake, DataBricks) Experience building tools for data engineering. In the US, the Base compensation range for this role is $ 154,445 - $185,334 . Actual compensation may vary based on level, experience, and skillset as assessed in the interview process. Benefits include equity, bonus (if applicable) and other benefits listed here . #LI-Remote *Compensation ranges are country specific. If you are applying for this role from a different location than listed above, your recruiter will discuss your specific market’s defined pay range & benefits at the beginning of the process. Why You’ll Thrive at Grafana Labs: 100% Remote, Global Culture - As a remote-only company, we bring together talent from around the world, united by a culture of collaboration and shared purpose. Scaling Organization – Tackle meaningful work in a high-growth, ever-evolving environment. Transparent Communication – Expect open decision-making and regular company-wide updates. Innovation-Driven – Autonomy and support to ship great work and try new things. Open Source Roots – Built on community-driven values that shape how we work. Empowered Teams – High trust, low ego culture that values outcomes over optics. Career Growth Pathways – Defined opportunities to grow and develop your career. Approachable Leadership – Transparent execs who are involved, visible, and human. Passionate People – Join a team of smart, supportive folks who care deeply about what they do. In-Person onboarding - We want you to thrive from day 1 with your fellow new ‘Grafanistas’ to learn all about what we do and how we do it. Balance is Key - We operate a global annual leave policy of 30 days per annum. 3 days of your annual leave entitlement are reserved for Grafana Shutdown Days to allow the team to really disconnect. *We will comply with local legislation where applicable. Equal Opportunity Employer: Grafana Labs is an equal opportunities employer. We welcome applications from everyone regardless of race, colour, nationality, origin, caste, sex, gender reassignment identity or expression, sexual orientation, age, religion or belief, disability, veteran status, genetic information, pregnancy, maternity, marital, family or carer status, or any other characteristic which is protected by local law. We believe that equality and diversity build a strong organisation, and we work hard to ensure that is the foundation of our organisation as we grow. Grafana Labs may utilize AI tools in its recruitment process to assist in matching information provided in CVs to job postings. The recruitment team will continue to review inbound CVs manually to identify alignment with current openings. #LI-Remote For information about how your personal data is used once you’ve applied to a job, check out our privacy policy .

Location: Baku Workplace: onsite ABOUT US   Xsolla is a global video game commerce company that provides a comprehensive suite of tools and services for game developers and publishers - including payments, distribution, game stores, launcher solutions, and partner network services. Our platform processes transactions across 200+ geographies, supporting thousands of games and millions of players worldwide. Quality is not optional - it is foundational to every product we ship. ROLE OVERVIEW The Director of QA is a senior technical leadership role responsible for owning and scaling Xsolla's quality engineering function across multiple product lines, teams, and time zones. You will define and drive the strategic vision for quality assurance - from test automation architecture and CI/CD integration to AI-assisted testing practices and performance engineering. You will lead a distributed organization of 30+ QA engineers and leads as part of a broader QA organization of 75+ professionals, ensuring predictable, high-quality releases across every product Xsolla delivers. This is not a management-only position. You must be deeply technical - capable of reviewing automation code, architecting test frameworks, debugging CI/CD pipelines, and evaluating AI-driven testing approaches hands-on. Key Responsibilities Strategic Leadership & Ownership Define and execute the QA strategy across all Xsolla products, aligning quality objectives with business goals and product roadmaps. Own QA deliverables end-to-end - from test planning through release sign-off - and be accountable for outcomes, not just activities. Establish and enforce quality gates, defect governance policies, and release readiness criteria across all product teams. Drive organizational maturity: evolve the QA function from reactive testing to proactive quality engineering embedded in every stage of the SDLC . Represent QA at the executive level - articulate quality risks, tradeoffs, and resource needs to VP/C-level stakeholders with clarity and data. Technical Excellence Architect and oversee enterprise-grade test automation frameworks spanning UI (Playwright), API, database validation (SQL), and performance testing (K6). Define and maintain standards for test code quality - including code reviews, PR contributions, reusable libraries, and modular test design. Deep understanding of Git workflows - branching strategies, merge request reviews, repository hygiene, and code versioning best practices across multiple repositories. Expert-level knowledge of CI/CD pipelines - design, optimize, and troubleshoot automated build, test, and deployment pipelines (GitHub Actions, GitLab CI, Jenkins, or similar). Ensure all automation is fully integrated into CI/CD pipelines, with clear pass/fail signals, automated regression gates, and performance benchmarks at every release stage. Drive adoption of infrastructure-as-code practices for test environments - containerized test execution, ephemeral environments, and environment parity between staging and production. Evaluate, select, and implement QA tooling - including test management platforms (Qase), observability tools, and defect tracking integrations. AI Integration & Innovation Proven track record of using AI in day-to-day QA activities - not aspirational, but demonstrated. You have used AI tools to generate test cases, write automation code, analyze test results, identify flaky tests, or accelerate debugging. Champion and operationalize AI-assisted quality engineering across the organization - specifically using Claude AI for code generation, test design, automation scripting, and documentation. Define governance frameworks for AI-generated test artifacts - validation, review, and sign-off processes to ensure AI outputs meet quality standards. Stay current with AI/ML advancements relevant to testing - intelligent test selection, predictive defect analysis, autonomous test generation, and self-healing automation. Establish metrics to measure the impact of AI adoption on QA velocity, coverage, and defect detection rates. Team Leadership & People Development Lead, mentor, and develop a distributed team of 30+ QA professionals - including QA Leads, Senior QA Engineers, and QA Engineers - across multiple time zones (Americas, Europe, Asia-Pacific). Build a high-performance culture rooted in ownership, technical excellence, continuous learning, and psychological safety. Conduct regular 1:1s, career development conversations, and performance reviews. Identify and grow future QA leaders. Design and implement onboarding programs, skill development paths, and technical training curricula - including AI literacy for all QA team members. Manage resource allocation and capacity planning across multiple concurrent projects, ensuring predictable and sustainable QA delivery. Navigate cross-cultural team dynamics with sensitivity and effectiveness - a truly global team requires a global leadership mindset. Process Rigor & Quality Governance Enforce rigorous QA processes across the organization:  • Test case management : Create, maintain, and execute comprehensive test cases in Qase with full traceability (pass, fail, blocked statuses). Bug documentation : Ensure all staging bugs are filed with detailed reproduction steps, expected vs. actual behavior, environment details, screenshots/videos, and severity classification - following established training standards. Automation framework documentation : Maintain clear, up-to-date documentation for all automation frameworks, ensuring any engineer can onboard and contribute. QA Score : Drive iterative improvements in QA Score metrics - tracking automation coverage, defect escape rate, test execution velocity, and regression stability. Define and track QA KPIs and OKRs - present quality dashboards and trend analysis to leadership regularly. Conduct root cause analysis on production escapes and implement systemic corrective actions. Cross-Functional Collaboration Partner closely with Engineering, Product, DevOps, and Release Management to embed quality practices into every phase of the development lifecycle. Work effectively in Agile/Scrum environments - participate in and drive sprint planning, retrospectives, daily stand-ups, and release ceremonies. Act as the primary QA stakeholder for cross-functional initiatives - environment strategy, deployment automation, incident response, and post-mortem processes. Build strong relationships with engineering leadership to ensure QA is not a bottleneck but an accelerator. Common Expectations Across All QA Roles Must be technical and able to write code for testing and automation. Use Claude AI to assist in code creation, automation, and test design. Follow QA processes rigorously: create and execute robust test cases in Qase , maintain clear documentation in automation frameworks, ensure traceability of executed test cases with statuses (pass, fail, blocked), and file Staging Bugs with detailed documentation following training standards. Contribute to iterative improvements in QA Score and testing processes. Strong communication and collaboration skills, analytical mindset, and commitment to continuous learning. Ability to work effectively in Agile/Scrum environments, participating in sprint planning, retrospectives, and daily stand-ups. Required Qualifications 15+ years of experience in QA/Quality Engineering , with at least 6+ years in Senior Manager or Director-level roles . Proven experience leading teams of 30+ people distributed across multiple time zones and cultural contexts. Hands-on technical proficiency - you can write and review test automation code, not just manage people who do. Proficiency in one or more: Python, JavaScript/TypeScript, Java. Deep expertise in test automation frameworks : Playwright, Selenium, Cypress, or equivalent for UI; REST/GraphQL API testing tools; database validation via SQL. Performance testing experience : K6, JMeter, Gatling, or Locust - designing, executing, and analyzing load/stress/soak tests. Expert knowledge of Git : branching strategies (GitFlow, trunk-based), pull request workflows, code review practices, repository management across multiple repos. Expert knowledge of CI/CD : designing and maintaining pipelines (GitHub Actions, GitLab CI, Jenkins, CircleCI), integrating automated tests into build/deploy workflows, debugging pipeline failures. Demonstrated use of AI tools in professional QA work - Claude, ChatGPT, Copilot, or similar - for test generation, automation coding, defect analysis, or process optimization. Provide specific examples. Strong understanding of Agile/Scrum methodologies and experience operating within and across Agile teams. Experience with test management platforms (Qase, TestRail, Zephyr, or similar). Excellent communication skills - ability to present complex technical quality topics to non-technical stakeholders, write clear documentation, and influence without authority. Bachelor's degree in Computer Science, Engineering, or related field (or equivalent practical experience). Preferred Qualifications Experience in the video game, fintech, or e-commerce/payments industry - understanding the unique quality challenges of high-throughput transaction systems. Experience with cloud-native architectures (GCP, AWS, Azure) and testing strategies for microservices, event-driven systems, and distributed architectures. Familiarity with containerization and orchestration (Docker, Kubernetes) for test environment management. Experience building or managing unified test environments - non-production environment strategies that enable safe, deterministic, and scalable validation. Knowledge of security testing fundamentals ( OWASP , penetration testing, vulnerability scanning). Experience with data pipeline testing and data quality validation. Background in establishing QA Centers of Excellence or transforming QA organizations from manual-heavy to automation-first. What Success Looks Like (First 12 Months) 90 days : Complete assessment of current QA processes, tooling, team capabilities, and automation coverage. Establish relationships with all QA leads and key engineering stakeholders. Identify top 3 strategic gaps. 180 days : Deliver a QA strategy roadmap aligned with product and engineering priorities. Implement measurable improvements in automation coverage and CI/CD test integration. Launch AI-assisted testing pilot across at least 2 product teams. 365 days : Achieve measurable reduction in production defect escape rate. Demonstrate >80% automation coverage on critical regression paths. AI-assisted testing practices adopted across all QA teams. QA Score trending consistently upward. Team engagement and retention metrics at or above company benchmarks. The duties and responsibilities of this position may evolve over time to support the organization’s goals and individual growth. This job description is intended to outline the general nature and level of work being performed and is not intended to be an exhaustive list of all duties, responsibilities, and qualifications required. By submitting your application, you consent to Xsolla conducting background checks, where permitted by law, after the final interview stage. All checks will comply with local regulations, and your information will be handled confidentially. Xsolla takes your privacy seriously and will not sell or externally distribute any personal data received during the hiring process. In accordance with applicable data protection laws, Xsolla is committed to protecting your personal information and respecting your privacy. For any inquiries related to data privacy, please contact: careers@xsolla.com Explore more opportunities at: https://xsolla.com/careers

Location: Hong Kong We are seeking a qualified and experienced Clinical Psychologist to join our growing team. The ideal candidate will have a strong background in delivering evidence-based treatments, particularly Cognitive Behavioral Therapy (CBT), and experience in administering neuropsychological assessments for youths, adolescents, and adults, as well as strong report writing skills.  Key Responsibilities: Develop and implement individualised treatment plans using evidence-based interventions, with a primary focus on CBT. Provide individual and group therapy sessions for clients, both in-person and virtually Conduct neuro-psychological assessments including ADHD, learning needs, dyslexia, and other related conditions. Participate in team meetings and contribute to ongoing service development and improvement initiatives. Collaborate with our interdisciplinary team to develop and implement client-centered treatment plans. Work closely with our 24/7 helpline responder team to manage risk, ensure the safety of clients in crisis situations and provide crisis interventions Maintain accurate and up-to-date client records in accordance with professional and legal standards. Continuously update professional knowledge and skills through participation in continuing education and Requirements Minimum Master’s Degree in Clinical Psychology with a minimum of 500 supervised hours of clinical experience post qualification (excluding academic placements) and ≥3 years of post-qualification clinical practice. Registered with appropriate local governing body such as HKPS Skilled in Trauma-Informed Therapeutic Approaches (e.g. TF-CBT, EMDR, DBT for trauma survivors, and/or Somatic Experiencing) and Cognitive Behavioral Therapy or other evidence-based approaches (e.g., Motivational Interviewing, DBT, SFBT). Experience managing moderate to high complexity cases. Hold valid and active licenses applicable to the country of practice. Proficiency in English and Vietnamese. Prior experience in EAP, therapy/counselling and/or as an in-house wellbeing provider is a plus. Benefits Why Join Us? Become part of a collaborative network of Clinical Psychologists dedicated to expanding access to quality mental health care. At Intellect, you’ll find a supportive community focused on enhancing lives and helping clients overcome personal challenges. If you’re ready to make a meaningful impact and be part of a mission-driven team, we’d love to hear from you. Apply today and join us in transforming mental health care!

Location: Remote, Canada; Remote, US GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role Site Reliability Engineers keep GitLab's user-facing services and production systems running reliably at scale. They combine software engineering with operational excellence, applying sound engineering principles, automation, and continuous improvement to build, operate, and evolve our production infrastructure. This is a single application for Site Reliability Engineering opportunities across Infrastructure Platforms. Rather than asking you to choose the right team or level upfront, we evaluate your skills holistically and match you to the opportunity that best aligns with your experience and our hiring needs. We hire Site Reliability Engineers from Intermediate through Senior Staff across multiple Infrastructure Platforms teams. We don't expect every candidate to have experience with every technology in our environment. We're looking for engineers with strong technical fundamentals, a growth mindset, and the ability to learn quickly. We'll support you in becoming successful with GitLab's tools, systems, and ways of working. Please note: This position is open to candidates based in the United States and Canada only. Candidates based in the United Kingdom can apply to this posting: Site Reliability Engineer, Infrastructure Platforms — UK (Intermediate to Senior Staff) How our SRE hiring works Because this is a single application for SRE roles across Infrastructure Platforms, our process is built to evaluate you once and match you well, rather than interviewing separately for every team. Recruiter Screen: A conversation about your background, what you're looking for, and the level and teams that fit, so we can point your process in the right direction. Core Technical: The shared assessment every SRE candidate takes, regardless of eventual team. A low-stress, collaborative discussion covering system architecture and incident review. Hiring Manager Interview: A conversation about ownership, judgment, execution, collaboration, and growth, the non-technical signals that make an SRE effective at GitLab. Peer Technical: Team-specific depth, run by SREs from the team you're most likely to join, focused on the problems that team actually works on. Skip-Level Interview: A conversation with a senior leader on values alignment, and how you'll work across teams. After your interviews, we consider your performance alongside our current hiring needs to confirm the level and team where you'll do your best work. Interview results are a major factor, and final placement also reflects our active hiring priorities at the time. We’ll calibrate your level throughout the interview process based on the scope and impact of your experience. Intermediate: You independently deliver meaningful reliability improvements within a defined area. Senior: You own complex reliability work end to end and raise the effectiveness of your team. Staff: You shape reliability across multiple teams, solving systemic problems and creating approaches others can reuse. Senior Staff: You set technical direction across a broader Infrastructure area and influence reliability strategy at organizational scale. What you'll do Keep user-facing services and production systems reliable, scalable, and efficient Build automation and tooling that reduces toil and replaces manual work with repeatable, infrastructure-as-code-driven workflows Operate and troubleshoot production systems on Kubernetes, including deployments, rollouts, and scaling Write and maintain infrastructure as code, and ship changes safely through CI/CD and GitOps Participate in on-call, triage alerts, follow and improve runbooks, and escalate appropriately Contribute to the observability stack, using metrics, logs, and SLOs to detect symptoms early rather than just outages Take part in incident response and post-incident reviews, turning learnings into changes in automation and process Document runbooks, architecture decisions, and reviews so your findings become repeatable practices What you'll bring Experience keeping production systems reliable, combining an operations mindset with real software engineering practice Experience building net-new infrastructure tooling and automation, not just configuring existing tools. For example, Terraform modules, Kubernetes operators or controllers, or production automation and services written from scratch The ability to read, debug, and reason about code. Most of our teams work in Go; some work in Ruby. You can discuss a piece of code's behavior, performance, and failure modes Experience with infrastructure as code, and with Kubernetes and its ecosystem, at a depth appropriate to your level Hands-on experience with at least one major cloud provider (GCP or AWS) Familiarity with observability practices, including metrics, logging, alerting, and SLOs or SLIs, and using data to inform operational decisions Comfort participating in on-call and incident response, with a structured approach to troubleshooting under pressure Strong written communication and the ability to operate as a manager-of-one in an async, distributed environment A track record of using automation, and increasingly AI, to reduce toil and improve how you and your team work Alignment with GitLab's values and a commitment to working in accordance with them About the team Infrastructure Platforms is responsible for the availability, reliability, performance, and scalability of GitLab’s user-facing services, most notably GitLab.com . The organization spans teams across Production Engineering , GitLab Dedicated , GitLab Delivery , and Developer Experience , covering everything from the production fleet and networking platform to observability, incident response, deployment infrastructure, tenant scale, and our single-tenant Dedicated offering. We are a globally distributed, remote-first organization that works asynchronously, favors automation over toil, and uses monitoring, metrics, and clear ownership to continuously improve the reliability of GitLab at scale. For more on how we work, see the Infrastructure Handbook Page . The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $126,400 — $314,400 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: San Francisco, CA | New York City, NY | Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Safeguards Enforcement Analyst on the user well-being team, you'll build and execute enforcement workflows that keep our products safe, with a focus on detecting and mitigating potential harm. Your initial focus will be on how Anthropic handles age. A core part of this work is making sure our consumer products reach the right audiences, including the detection signals, verification paths, and appeals workflows that keep underage users off surfaces not designed for them. Claude also reaches younger users through third-party developers building on our API, and you'll be the enforcement partner that sales and platform teams rely on when those customers need guidance on deploying age-appropriately. This position may expand into broader areas of user well-being enforcement over time. Safety is core to our mission, and you'll help shape policy enforcement so that our users can safely interact with and build on top of our products in a harmless, helpful, and honest way. Important context for this role: In this position you may be exposed to and engage with explicit content spanning a range of topics, including those of a sexual, violent, or psychologically disturbing nature. There is also an on-call responsibility across the Policy and Enforcement teams. Key responsibilities Design and architect automated enforcement systems and review workflows that scale effectively while maintaining high accuracy Partner with Engineering and Data Science teams to optimize detection models for policy violations and automated enforcement systems Review flagged content to drive enforcement and policy improvements Enforce usage policies with a focus on detecting and mitigating potential harmful use of AI systems Work with Legal, Public Policy, and Privacy stakeholders to keep our age assurance approach proportionate, privacy-preserving, and responsive to an evolving regulatory landscape Support the Safeguards policy design team by providing detailed feedback on policy gaps based on real enforcement scenarios Keep up to date with emerging AI policy enforcement best practices, and use these to inform our decision-making and workflows Responsible for Anthropic's layered age assurance approach - self-declaration, behavioral signals, verification, and ban appeals - to keep our first-party consumer products safe Adjacent user well-being enforcement where age is a key factor in how policy is applied such as sexual content and illicit substances Minimum qualifications Experience in trust and safety, online child safety, age assurance, privacy, product policy, or a related field Subject matter expertise in one or more of: age assurance or age verification systems, age-appropriate design, child online safety, privacy-preserving verification methods, or content classification for young people Experience driving cross-functional initiatives with Product, Engineering, Legal, and Policy partners — especially where safety, privacy, and usability tradeoffs need to be navigated together Experience navigating evolving regulatory landscapes and enforcement best practices with regards to age assurance (including frameworks like the UK AADC, COPPA, and the DSA), CSAM/CSEM, NCII, and digital well-being A thoughtful perspective on the privacy/safety tradeoffs inherent in age verification — including when less invasive approaches are the right call Strong written communication skills, with experience producing clear briefs and recommendations for technical and non-technical stakeholders Comfort using data (SQL or similar tools) to measure what's working and inform decisions Excellent judgment and the ability to collaborate with team members while navigating rapidly evolving priorities and workstreams Preferred qualifications Experience building or operating age-gating flows, age estimation signals, underage account detection, or appeals workflows Experience advising or partnering with third-party platforms on deploying safely to younger users Experience working with or evaluating third-party age verification providers A deep interest in AI safety and responsible technology development Experience writing effective prompts for generative AI systems in a content review or enforcement context 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: $245,000 — $285,000 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.