Вакансии

Location: Remote - US About LaunchDarkly Engineering LaunchDarkly helps engineering organizations ship software and AI with speed, safety, and control. Our platform gives teams the confidence to release gradually, target experiences to the right audiences, learn through experimentation, understand what is happening in production, and respond quickly when risk appears. Our engineers build the systems, services, SDKs, developer tools, cloud infrastructure, and product experiences that make this possible. The work spans high-scale distributed systems, reliable data and event pipelines, intuitive enterprise workflows, and AI-powered capabilities that help teams manage the next generation of software delivery. LaunchDarkly’s SDKs are used in systems that perform trillions of feature flag evaluations each day, giving our engineering work a direct connection to the reliability and customer experience of software around the world. As the company grows, we are expanding beyond traditional feature management into experimentation, observability, and AgentControl—helping customers control more of the software and AI lifecycle. That creates an unusually broad set of technical challenges, visible customer impact, and room for engineers to shape what comes next. We believe in the power of teams. We work with humility, openness, curiosity, and care; we value clear communication, thoughtful technical judgment, inclusive collaboration, and a strong sense of ownership. We encourage people to apply even when they do not meet every qualification listed below. We are interested in the experience, perspective, and potential you would bring to the role. About the Job As a Software Engineer on LaunchDarkly’s SDK team, you will build the primary touchpoint that our customers interact with on a daily basis. You’ll work with multiple technologies across our 35+ SDKs while enabling customers of all kinds to feature flag their code. When working on our SDKs, you’d be contributing to much more than thin client wrappers. Our SDKs are feature-rich agents with strong emphases on performance, concurrency, and resiliency -- all while following idiomatic practices for their tech stack. LaunchDarkly serves trillions of feature flags daily to customers all around the globe, and every flag is handled by our SDKs. This team has a major impact not only on our company, but on our customers (and their customers). We are growing fast and we need your help writing the next chapter in our story. Responsibilities: Contribute to development for SDKs in supported platforms : Implement new features and improvements to meet customer performance and resiliency requirements Keep up to date with the latest development practices Collaborate with our engineering and product teams to drive the implementation and release of major features Actively maintain our open-source repositories Identify areas of improvement and advocate for best practices Have an active voice in shaping both technology and product decisions Basic Qualifications: Demonstrable experience building libraries and packages used by other developers Polyglot background with an ability to context switch between languages quickly 5+ years experience with at least two of the following: .NET/Go/Ruby/Python/NodeJS/Java Experience with the following is a plus: C++/Erlang/Haskell/Lua AI SDKs Observability SDKs Mobile development Strong computer science fundamentals Committed to working in a communicative, collaborative environment Self‐starter and problem solver, willing to solve difficult problems and work independently when necessary Strong testing background: experience building unit, integration, load tests, and benchmarks Experience writing production-ready code with emphasis on quality and maintainability Experience contributing to open-source software Logistics: This is a remote role, with opportunities to visit the office in the Bay Area, California, for team offsites The SDK team is spread between Eastern and Pacific time zones Highlights: You will work collaboratively with a team of highly experienced engineers who are amazing at the craft of engineering and building SDKs Your contributions will be publicly visible as the SDK team develops LaunchDarkly’s open-source SDKs in public LaunchDarkly uses our own SDKs. You will have opportunities working with the other teams within LaunchDarkly In this role, you can learn about many programming languages and frameworks You will have opportunities to strongly influence roadmap and prioritization Pay: Target pay ranges based on Geographic Zones* for Level 3: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $171,200 - $235,400** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $154,100 - $211,860 ** Zone 3: All other US locations - $ 145,500 - $200,090 ** LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: Denmark - Remote; Sweden - Remote Chainguard is the trusted source for open source. By delivering hardened, secure, and production-ready builds of all the open source software engineers and AI agents rely on, Chainguard helps organizations build faster, stay compliant, and eliminate risk. Our customers include Fortune 500 enterprises and global industry leaders, including Anduril, Canva, Fortinet, Hewlett Packard Enterprise, OpenAI, Snap Inc., and Snowflake. Chainguard is venture-backed by leading investors, including Amplify, IVP, Kleiner Perkins, Lightspeed Venture Partners, Mantis VC, Redpoint Ventures, Sequoia Capital, and Spark Capital. The role, in a nutshell: Chainguard is building a safer foundation for software. We work with security and engineering teams who care deeply about supply chain security, open source, and modern infrastructure. We’re looking for a BDR who already knows how to run outbound, and is ready to take it further into more technical conversations, more complex organizations, and more strategic account development. This role is about earning attention from engineers and security leaders , not just landing meetings. You’ll partner closely with enterprise AEs to break into high-value accounts and build pipeline that actually converts. What you’ll do: Drive enterprise account strategy - Work alongside AEs to map target accounts and identify the right entry points across security, platform, and engineering teams. Run thoughtful, technical outbound - Craft highly personalized outreach that resonates with developers, DevOps, and security leaders — no generic sequences. Understand how modern infrastructure works - Research how companies build and ship software (containers, CI/CD, cloud environments) to make your outreach relevant and credible. Lead meaningful early conversations - Qualify opportunities by understanding technical context, risk posture, and business priorities. Build real pipeline, not just meetings - Focus on creating opportunities that move forward — quality over quantity. Act as an extension of the AE - Collaborate on account plans, messaging, and deal progression. Use tools intelligently - Leverage Salesforce, Outreach/Salesloft, and data tools to execute efficiently — but never at the expense of quality. Continuously improve the motion - Test messaging, share insights, and help refine how we engage the market. Be a feedback loop to the business - Bring insights from conversations back to marketing and product — especially what resonates (or doesn’t) with technical buyers. What we're looking for: At least 6 months of BDR/SDR experience (or equivalent transferrable experience) Proven ability to generate pipeline through outbound (not just inbound qualification) Experience engaging multiple stakeholders within technical or complex organizations Strong writing skills — especially in crafting personalized, relevant outreach Curious and motivated to learn how modern software and security actually work Comfortable navigating ambiguity and building your own approach Experience with Salesforce, Outreach/Salesloft, or similar tools Track record of hitting or exceeding pipeline targets What makes this role compelling: Sell something technical buyers respect — security + open source + developer-first Go deeper technically — engage with real infrastructure and security problems Operate as part of the deal team — not just top-of-funnel support Have real impact on revenue — not just activity metrics Compensation: $100,000 OTE About Us We live and breathe our company values: We are customer obsessed — We focus on delivering solutions to our customers that create value and make their lives better. We have a bias for intentional action — We prioritize, plan, try things, and fail fast. We don't take ourselves too seriously (but we do serious work) — We are solving an important problem which takes focus, but we also like to enjoy the journey. We trust each other and assume good intentions — We're transparent with decisions to empower team members to make well informed decisions. A few of the benefits we offer: Flexible & Remote-First Culture: Work remotely with team meetup opportunities, bi-annual destination summits, and a monthly stipend for coworking spaces, phone and internet costs. Our Approach to Equity: Receive stock options upon hire and promotion. Plus, you can participate in secondary offerings and have 10 years to exercise your options (yes, you read that correctly: 10 years!). 100% Covered Health Insurance: We cover 100% of your health, vision and dental insurance premiums for you and your dependents. Nothing comes out of your paycheck. ∞ Flexible Time Off: Take the time you need – to do our best work, we need to recharge and reset. 18 Weeks Paid Parental Leave: We offer 18 weeks for birthing parents and 12 weeks for non-birthing parents, with the option to use it all at once or throughout your child's first year. If your experience is close but doesn't fulfill all requirements, please apply. We're building the best team in technology and are focused on hiring "Chainguardians" with unique backgrounds, perspectives, and experiences. Chainguard is an equal opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. By submitting your application, you acknowledge that Chainguard will process your personal data in accordance with Chainguard's Global Candidate Privacy Notice . ©2026 Chainguard. All Rights Reserved.

Задачи Донастройка системы после подрядчика: VM, внутренние и сервисы, доступы. Эксплуатация: аптайм, мониторинг, инциденты.

Location: Russia; Moscow; Perm Workplace: remote ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. The role THE ROLE We are hiring a Senior Backend Engineer for two platform products: Xsolla ID is the identity and authentication platform behind sign-in, account management and SSO across Xsolla products. Xsolla ZK is Web3 wallet infrastructure: smart wallets and account abstraction on a zkSync-based L2. Both products sit on users' most sensitive flows, logging in and signing transactions, and other Xsolla teams build on top of them. WHAT YOU WILL OWN The backend services of your product area end to end: design, implementation, release and production operation, including on-call Architecture across services: service boundaries, integration contracts and data ownership. You make these decisions and justify them in writing Reliability and security of critical flows: SLOs, failure handling, protection of user data and credentials Service performance and cost under load WHAT YOU WILL DO Design and build services and APIs (REST, gRPC) for authentication, account management and wallet operations Define service boundaries and integration contracts with other Xsolla teams Design data models and storage; optimize schemas and queries Build event-driven and asynchronous workflows Own observability: metrics, logs, tracing and alerting, and act on what production tells you Take part in on-call, incident response and post-mortems Improve the engineering environment: CI/CD, infrastructure-as-code, testing Review code Set up and maintain AI tooling in the repositories (Claude Code, Codex, Cursor: rules, context, harness) so the team uses it effectively Responsibilities Language and platform 5+ years of commercial backend development Go: idiomatic code, concurrency (goroutines, channels, context and cancellation), memory and performance profiling (pprof) Data Relational databases (PostgreSQL, MySQL): schema design, indexes, query plans, transactions and isolation levels, safe migrations Caching (Redis): when to cache, invalidation, consistency trade-offs Distributed systems Service architecture and distributed-systems trade-offs: consistency, availability, idempotency, retries, failure modes Asynchronous messaging and event-driven design (Kafka, RabbitMQ or NATS): delivery guarantees, ordering, reprocessing APIs Designing REST and gRPC APIs: versioning, backward compatibility, contract documentation (OpenAPI / Swagger, Protobuf) Security and identity Application security: common vulnerability classes (OWASP Top 10), secrets management, safe handling of user data OAuth 2.0 / OIDC from the server side: flows, tokens, sessions Operations Containers and orchestration (Docker, Kubernetes) at the level of deploying and debugging your own services Observability (we use Datadog; experience with Prometheus, Grafana, ELK / Graylog or OpenTelemetry also counts): metrics, logs, tracing and alerting; diagnosing incidents in production Engineering practices Testing: unit, integration, contract Git, CI/CD (GitLab CI or similar) AI-assisted engineering Daily hands-on use of AI coding tools (Claude Code, Codex, Cursor) for development and review, including configuring them for a repository English Reading technical documentation in English Nice to Have Web3 backend experience: blockchain integration, wallet infrastructure, account abstraction High-load systems Cloud platforms (GCP, AWS or Azure) and infrastructure-as-code NoSQL databases (MongoDB or similar) Domain experience in gaming, e-commerce, fintech or payments HOW WE WORK Decisions in writing. Significant technical decisions are written up as an RFC or ADR that lays out the options and trade-offs. We discuss the document, not a blank whiteboard. AI is part of everyday engineering. We use AI coding tools for development and review, and we treat configuring them for a codebase as real engineering work. HOW WE HIRE Intro call. Your background, your motivation and the role. Technical interview. Built directly on the What you will own and Required sections above. We won't ask about anything this posting doesn't promise. Bar raiser. An engineer from outside the hiring team checks that you raise the overall engineering bar. THE TEAM You will work alongside product managers, designers, backend and frontend engineers, QA and DevOps. BENEFITS We are passionate about fostering a supportive environment for our team, so we prioritize the physical, mental, and emotional well-being of our employees and their families through a comprehensive Benefits Program. This includes medical, dental, and vision, PTO, and a personalized career roadmap for each employee. By investing in professional development through training and educational opportunities, we ensure that our team thrives both personally and professionally. Together, we're not just building a business; we're cultivating a community that values creativity, collaboration, and the transformative power of play. EMPLOYMENT DETAILS Location: Remote Employment Type: Full-time Schedule: 10:00–19:00 (flexible) Contract: Employment agreement (entity or EOR arranged per candidate location) EQUAL EMPLOYMENT STATEMENT Xsolla is dedicated to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, language, sexual orientation, national origin, genetics, political beliefs, disability, age, marital status, social background or other characteristics. We are committed to compliance with all fair employment practices regarding citizenship and immigration status. CONTACT If you have questions regarding our hiring practices, please contact careers@xsolla.com. For more vacancies, visit xsolla.com/careers.

Design and build production RAG systems and AI agents. Run open-source LLMs self-hosted, from model selection to serving and optimization.

Имеет опыт от 5 лет разработки на языке C# (язык программирования C#), проектированием и эксплуатацией веб-сервисов. Имеет опыт работы с большими объёмами данных в базах данных.

We are looking for a Senior Platform Engineer on behalf of our client to build, scale, and maintain an Internal Developer Platform (IDP) that empowers application software teams to ship code safely, independently, and rapidly. Maintain cluster health, upgrade lifecycles, autoscaling policies, and security policies across multi-region Kubernetes deployments.

Design and develop end-to-end data pipelines using Azure Data Factory, SQL, and other Azure services. Implement complex data models, DAX measures, and calculated columns to support reporting.

We are looking for a Senior Cloud Engineer specializing in Microsoft Azure on behalf of our client to design, automate, and maintain high-availability cloud infrastructure. Architect and deploy enterprise-grade Azure infrastructure using Terraform/Bicep, maintaining modular IaC libraries and strict state management workflows.

You’ll be responsible for building modern and scalable web applications, working closely with backend developers and designers to create intuitive user experiences.

В команду по производству напольных покрытий ищем Программиста 1С:ERP для развития функционала существующей инсталляции 1С:ERP. Доработки и развитие базовых модулей ERP (БУНУ, МСФО, закупки, продажи, склад, производство);

Location: 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 largest and fastest-growing infrastructure fleets in the industry — 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 one of Anthropic’s largest areas of spend. 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. Utilization improvements are worth enormous sums at our scale. 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 exabyte 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: New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — 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 one of Anthropic’s largest areas of spend. 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. Utilization improvements are worth enormous sums at our scale. 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 exabyte 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: Paris, France Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs. About the client Our client is a leading player in the online gaming and betting industry, operating one of the largest poker and sports betting platforms in Europe. Their platform serves hundreds of thousands of active users monthly and relies on highly scalable, real-time distributed systems designed to handle massive traffic volumes with high availability and low latency. The company combines strong technical excellence with a fast-moving product environment and offers engineers the opportunity to work on complex distributed architecture challenges at scale. About the Role We are looking for an experienced Senior Backend Engineer to join the Poker engineering team and contribute to the d e sign, development , and optimization of highly scalable microservices powering a large-scale real-time gaming platform. You will work on distributed, event-driven systems handling high-throughput traffic and real-time messaging workloads, while collaborating closely with infrastructure, frontend, data, and security teams. This role is ideal for engineers passionate about backend architecture, scalability, distributed systems, and high-performance platforms. Contract : PERMANENT - CDI Model : Onsite, 4 days week! Location : Paris, France (75007) Hiring Process: 4 interviews - HR screening, 2 Technical Interviews, Final Meeting and Offer Discussion NOTE: high preference for candidates who attended CPGE scientifiques — Classes Préparatoires aux Grandes Écoles scientifiques. Key Responsibilities Design and evolve the architecture of distributed backend systems Develop highly available and scalable microservices Build and maintain APIs and data models Work on real-time event-driven systems with high throughput requirements Implement unit, integration, and end-to-end testing Participate in code reviews and technical discussions Deploy and maintain services in AWS environments Monitor, troubleshoot, and optimize platform performance Contribute to architecture and technical documentation Collaborate with Frontend, Data, Infrastructure, Security, and Product teams Requirements Significant experience in developing back-end services on a high-traffic platform (10K+ req/s) Significant experience with load balancing, high availability, scaling, caching, database, and storage issues Proficiency in event-driven distributed architectures Proficiency in Redis or Kafka (data structures, pub/sub, streams, pipelines) Proficiency in relational databases (MySQL or PostgreSQL), modeling, optimization, transactions, and locks Knowledge of JavaScript and the Node.js ecosystem is desirable (microservices rely on Node.js) Knowledge of the cloud environment DevOps culture (CI/CD, Docker, Observability) Mandatory academic background from CPGE scientifiques (Maths Sup / Maths Spé) Benefits Permanent full-time contract (CDI) 4-day work week Profit-sharing and participation programs Company restaurant On-site gym facilities Long-term growth opportunities Modern engineering culture focused on scalability and innovation

проектирование, разработка и поддержка высоконагруженных backend-систем; сопровождение и мониторинг работы сервисов в продуктивной среде;

Тестировать функциональность продукта на веб и ТВ-платформах: от главной страницы и плеера до личного кабинета. Проверять сценарии подписки и платежей: оформление, автопродление, отмена, возвраты, граничные состояния.

Сопровождение ML-решений (мониторинг сервисов и моделей, отслеживание дрейфа данных, работа над развитием); Оценка влияния на бизнес предложенных решений;

Задачи: Вести людей и команду: регулярные 1:1, развитие, обратная связь, рост инженерной планки; Планировать delivery вместе с продуктом/аналитикой: приоритеты, декомпозиция, оценки, риски, прогнозируемость;