Вакансии

We're looking for experienced software engineers to build AI coding tasks from a codebase they know well. You turn a real change from a repository you know into a task that today's best AI coding models struggle with: hard for the models, but fair for a skilled engineer.

Location: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance—so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started—and we need exceptional engineers to help us build the backbone of the future of agent-based development. _______________________________________________________________________ WHAT YOU’LL DO - Design and implement core systems powering the AI Gateway, including the model router, MCP gateway, and control plane - Build infrastructure that supports dynamic model selection/routing, auto-failover, cost-based routing, and policy enforcement - Own critical capabilities such as secure credential storage, session summarization, caching, and rate limiting - Develop APIs for developers building with OpenAI-compatible interfaces and the Model Context Protocol - Build the underlying infrastructure to support evaluation, telemetry, replay, and backtesting for agents and LLM workflows - Lead architectural decisions and mentor engineers as the team scales - Performance tuning - caching, session summarization, and rate limiting that keep the gateway fast under real production load - Contribute to roadmap planning, technical strategy, and cross-functional alignment KEY PROBLEMS YOU’LL HELP SOLVE - Building a unified abstraction over fundamentally different model and tool providers without leaking their differences into the developer experience - Making credential and identity handling for tool access both airtight and fast - Giving developers real-time and historical visibility into what their agents are doing, with policy enforcement that can't be bypassed - Keeping latency low and reliability high as traffic scales from early adopters to production fleets - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ WHO YOU ARE Required Qualifications: - 6+ years of backend engineering experience with production-grade systems - Deep knowledge of distributed and highly scalable systems, cloud-native infrastructure, and API design - Experience building secure, high-throughput services (e.g., gateways, proxies, load balancers, policy engines) - Fluency in Go, and/or Rust (both preferred) - Familiarity with AI/ML platforms or model serving infrastructure - A strong product mindset—you're excited about building developer-facing tools - Ownership mentality with a bias for shipping, learning, and iterating - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience Bonus Qualifications: - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture _______________________________________________________________________ WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $160,900 – $260,700 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA or Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker AI Gateway is our answer to the complexity of taking AI agents from prototype to production. It’s a powerful, intelligent, and secure control point that eliminates the toil of model orchestration, tool management, observability, and governance - so developers can focus on building incredible AI agents, not gluing together infrastructure. The Gateway sits at the center of modern AI applications, offering: - A model and tool routing layer with built-in security and cost optimization - A familiar OpenAI-compatible interface and MCP server - Unified observability and policy enforcement - Auto-RAG, tool injection, session summarization, and more We’re just getting started and we need exceptional engineers to help us build the backbone of the future of agent-based development. _______________________________________________________________________ WHAT YOU’LL DO - Set technical direction for core systems powering the AI Gateway 0 the model router, MCP gateway, and control plane - and make sure architectural decisions hold up as usage scales by 10x - Consistently identify gaps in our infrastructure, process, or tooling before they become blockers, and drive the fix from idea to production - Take a significant, hands-on role in defining, delivering, and implementing the Gateway's technical strategy, in close partnership with engineering leadership - Own the hardest, highest-ambiguity problems in the system: dynamic model selection, auto-failover, cost-based routing, and policy enforcement that has to work end-to-end - Act as the go-to expert for secure credential storage, session summarization, caching, and rate limiting - the capabilities everything else depends on - Build the infrastructure that lets us, and our customers, evaluate, replay, and backtest agent and LLM behavior with confidence - Mentor senior and mid-level engineers, and raise the technical bar for the team through code, design review, and example - Partner with product, design, and leadership to shape not just what the control plane UI does, but where the product goes next KEY PROBLEMS YOU’LL HELP SOLVE - Define the unified abstraction layer across diverse model and tool providers (OpenAI, Anthropic, Google, AWS Bedrock) that the rest of the org builds on - Architect secure, scalable identity and credential vaulting for tool and model access, trusted enough to run at enterprise scale - Build the infrastructure for real-time and historical analytics of AI agent behavior that leadership and customers both rely on - Guarantee that policy enforcement and logging work end-to-end - from prompt to tool to response - with no gaps an auditor (or attacker) could find - Set the bar for developer experience through intuitive APIs and first-class observability - Take part in on-call rotation for your team, respond to incidents, debug production issues, and drive continuous improvement of system reliability _______________________________________________________________________ WHO YOU ARE Required Qualifications - 8+ years of backend engineering experience, with a track record of owning production-grade systems at significant scale - Deep specialization in distributed systems, cloud-native infrastructure, and API design - recognized by peers and cross-functional partners as a go-to expert, not just experienced - Experience building secure, high-throughput services (gateways, proxies, load balancers, policy engines), and a history of making judgment calls other engineers rely on - Fluency in Go and/or Rust - A track record of identifying systemic gaps - in architecture, process, or tooling-— and driving the fix across team boundaries, not just within your own - A strong product mindset, with real experience shaping technical direction rather than only executing against it - Comfortable operating with wide latitude: given a problem and significant autonomy in how to solve it, including when and who to pull in - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience BONUS QUALIFICATIONS - Prior experience with OpenAI, Anthropic, or similar LLM APIs - Familiarity with RAG architectures, vector databases, or agent frameworks (e.g., LangChain, AutoGPT, CrewAI) - Experience with policy engines (e.g., OPA), observability frameworks (e.g., OpenTelemetry), or API gateways - Understanding of OAuth 2.1, secret management, and cloud IAM systems - Experience with Kubernetes, Docker, and microservices architecture - A track record of setting technical standards that other teams or engineers went on to adopt _______________________________________________________________________ WHY JOIN US? - Work on what’s next: The agent era is just beginning. Help define the infrastructure stack for the next generation of software. - Own mission-critical infrastructure: Be part of a small team building the backbone of secure, intelligent agent applications. - Impact at scale: Your work will touch tens of thousands of developers building AI-first applications. - Engineering excellence: Join a world-class engineering team that values simplicity, code quality, and deep technical thinking. - Remote-first culture: Work from anywhere with a team that trusts and empowers you. Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $170,350 – $275,550 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: Lisbon; Portugal Workplace: Hybrid ROLE HIGHLIGHTS: - Role: Forward Deployed AI Engineer - Department: Forward Deployed Engineering - Location: Portugal (Lisbon) - Reports to: VP, Forward Deployed Engineering - Working type: Hybrid (On-site at customer locations approx. 50% of time) - Must be eligible and able to attain relevant national and NATO security clearances. - Must be based in-country and native level speaker of the country you're deploying to. THE MISSION OF THE FORWARD DEPLOYED AI ENGINEER In this role, you'll be the hands-on AI builder defense and intelligence customers rely on. You’ll deploy ICEYE’s intelligence platform into secure (often air-gapped) environments and rapidly ship AI-powered workflows on top of it—everything from Docker-based deployments to RAG systems fusing SAR imagery with intelligence reports. This is a ship-code-daily role: turning raw satellite data into mission-critical tools analysts use to protect nations. WHO WE ARE ICEYE is the world leader in sovereign intelligence from space. We deliver persistent monitoring capabilities to detect and respond to changes in any location on Earth. ICEYE owns the world's largest and most advanced SAR (synthetic aperture radar) satellite constellation. To our customers we provide intelligence with unmatched quality, latency and revisit times, in any weather, day or night. To governments who choose to operate their own constellation we provide this proven capability as a sovereign system. ICEYE-built constellations serve customers in defence and intelligence, environmental monitoring, insurance and emergency management. We enable fast decisions that contribute to a safer future. Founded and headquartered in Finland, ICEYE operates globally with over 1000 employees across Europe, North America, the Middle East, and Asia-Pacific. DAY TO DAY RESPONSIBILITIES: PLATFORM DEPLOYMENT & INTEGRATION - Deploy ICEYE's intelligence platform into customer secure environments (on-premise, air-gapped networks, classified data centers). - Build and maintain containerized applications (Docker) and manage deployments in customer Kubernetes clusters. - Develop APIs and data pipelines connecting ICEYE systems to customer C4ISR infrastructure and intelligence tools. - Troubleshoot deployment issues in disconnected environments without external internet access. AI SOLUTION DEVELOPMENT & CUSTOMIZATION - Build Retrieval-Augmented Generation (RAG) systems that combine ICEYE SAR data with customer intelligence documents for context-aware analysis. - Develop AI agents and workflows using frameworks like LangChain, LangGraph, or similar tools to automate analytical tasks. - Implement prompt engineering strategies and conversational AI interfaces that enable analysts to query satellite data using natural language. - Create Model Context Protocol (MCP) integrations connecting AI systems with customer data sources. DATA FUSION & INTELLIGENCE WORKFLOWS - Build data fusion pipelines combining SAR imagery with additional intelligence sources (AIS, RF signals, optical imagery, SIGINT). - Develop automated workflows that correlate and cross-reference information across different data modalities. - Create lightweight tools, dashboards, and alerting systems tailored to customer operational needs. CUSTOMER ENGAGEMENT & RAPID PROTOTYPING - Work embedded with intelligence analysts, data scientists, and military operators to understand mission-critical problems. - Rapidly prototype AI-powered solutions (code first, polish later) that address immediate operational requirements. - Conduct hands-on training sessions on platform capabilities and AI workflow usage. - Gather customer feedback and translate it into technical requirements for ICEYE's product and engineering teams. WHAT WE ARE LOOKING FOR MUST HAVE SKILLS: - 3+ years hands-on software engineering building and deploying production systems. - Strong Python programming skills (required) plus one of: Go, TypeScript, or Rust. - Hands-on experience with LLMs, prompt engineering, and RAG systems. - Working knowledge of agent frameworks (LangChain, LangGraph, pydantic-ai) and vector databases. - Experience with Docker and deploying in secure / isolated / air-gapped environments. - Practical experience with APIs, data pipelines, and integrating systems in production, - Familiarity with Linux and basic Kubernetes operations. - Builder mindset: ship fast, iterate with feedback, and prioritize working solutions over perfect architecture. - Strong communication + customer engagement, able to work embedded with intelligence analysts / military operators. - Strong spoken and written English, able to explain technical concepts to non-technical stakeholders. - Willingness to travel 40–60% to customer sites within the region. NICE TO HAVE SKILLS: - Experience in defense, intelligence, or government operational environments. - Deploying to on-prem data centers and/or air-gapped networks. - Familiarity with geospatial data, satellite imagery, or remote sensing. - Experience with MCP integrations, multi-agent systems, or agentic workflows. - Deeper Kubernetes, IaC (Terraform/Ansible), and/or offline CI/CD. - Understanding of intelligence analysis workflows and defense/government requirements. - Experience with data fusion, multi-source intelligence integration, or GIS tools (ArcGIS, QGIS). - Background in solution engineering, technical consulting, or customer success. - Experience in defense tech (e.g., Palantir, Anduril, Scale AI, similar startups). APPLICATION PROCESS - Talent Acquisition Interview - Take home task - Hiring Manager Interview - Hiring Team Interview - Offer Decision WORKING AT ICEYE At ICEYE, you’ll join a diverse and highly engaged team united by the ambition to make the impossible possible. As a global scale-up, we combine speed and ambition with the opportunity to take real ownership from day one. Your growth, wellbeing, and success are a priority, with continuous professional development, training opportunities, and a culture where collaboration is how we win. HOW WE WORK (OUR VALUES) Make the impossible possible: We set ambitious goals and stay calm under pressure. We bring grit, optimism, and ownership when things get hard, and we keep moving until we find a way. - Be curious: Go deep, ask questions, listen carefully, and think critically. Understand the “why” behind decisions. - See the big picture: Stay close to what’s happening across the company so you can make better decisions. Consider how your work affects others. - Drive effective teamwork: Create psychological safety, invite different perspectives, and build inclusive teams. There are no bad questions. - Act as one team: We win together. We match tasks to the right owner and stay agile as priorities shift. - Have fun: What we do matters—and it should be enjoyable. Celebrate progress, take pride in results, and share the wins. BENEFITS Our benefits are designed to support your health and wellbeing—at work and beyond. We keep improving them based on employee feedback, and offerings vary by location. Talent Acquisition will confirm what applies for this role and location during the process. OUR COMMITMENT TO DIVERSITY, EQUITY AND INCLUSION We want ICEYE to be a place where people can be themselves and do great work. Different backgrounds and perspectives make us stronger, which is why we work to create an environment where people feel included, respected, and able to speak up. Whatever your background, we want you to bring your authentic self to the table. We’re committed to fair, inclusive hiring and equal opportunity. Everyone is welcome to apply. If you need any adjustments or support during the recruitment process, tell us—we’ll do our best to help. Apply now to start your ICEYE journey, and help us continue to make the impossible possible together. Read more about ICEYE and working with us at iceye.com https://www.iceye.com

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients. The AI Infrastructure team builds and operates the production systems that power intelligent agents at scale. This team sits at the foundation of the agent platform, ensuring that model inference, orchestration, and execution layers are reliable, observable, and performant under real-world load. Working closely with the Agent Systems team and broader infrastructure partners, this group owns the core primitives that enable agents to safely operate across internal systems. The environment is high-scale and high-stakes — systems serve millions of users and must meet strict reliability, latency, and correctness standards. This is a deeply production-oriented team. Engineers here combine strong systems thinking with applied ML infrastructure experience, building in Rust and operating services where performance and failure modes matter.   THE OPPORTUNITY - Design and build the infrastructure layer powering AI agent systems in production - Develop high-performance services that handle model inference, orchestration, and execution - Architect scalable systems capable of supporting millions of users and high request throughput - Build reliable ML infrastructure and MLOps patterns for model deployment, evaluation, and monitoring - Define guardrails, observability, and failure handling for agent-driven workflows - Optimize latency, throughput, and cost across inference and orchestration layers - Partner closely with the Agent Systems team to translate experimental prototypes into hardened production systems - Contribute to foundational infrastructure decisions in a high-scale, high-impact environment   WHAT YOU BRING - 5+ years of experience building and operating high-scale production systems - Strong Python skills and the ability to reason about systems performance and reliability - Deep understanding of distributed systems, reliability engineering, and performance optimization - Experience operating services serving millions of users or high-throughput workloads - Familiarity with ML infrastructure, model serving, or MLOps in production environments - Experience designing observability, monitoring, and failure recovery systems - Strong collaboration skills working across infrastructure and applied engineering teams - High ownership mindset in high-stakes production environment   NICE TO HAVES - Experience with Rust - Experience building infrastructure for agent-based or LLM-powered systems - Background in high-performance networking, async systems, or low-latency architectures - Experience with container orchestration and cloud-native infrastructure - Familiarity with evaluation frameworks and model performance monitoring at scale - Experience working in fast-moving 0→1 or platform-building teams Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on X https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: San Francisco We’re looking for an enterprise-focused value consultant to partner directly with Asana’s top enterprise customers and help them align on value and ROI across their entire customer lifecycle . As a member of our Business Value Consulting team, you will build bespoke pre-sales business cases, drive post-sales value realization, and quantify multiyear proposals to showcase the impact of an Asana investment . You’ll also work cross-functionally across Sales, Solutions, Customer Success, and Marketing to build scalable value assets, thought leadership, and enablement materials that elevate our team's value motions across the company . This role can either be fully remote depending on which US state you live in, or based in our San Francisco, New York, or Chicago office with an office-centri c hybrid schedule . If based in-office: The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do and the teams with which you partner . If you're i nterviewing for this role, your recruiter will share more about the in-office requirements . What you’ll achieve Build direct, strategic partnerships with Asana’s top enterprise customers throughout their lifecycle . Create bespoke, in-depth business cases that quantify hard benefits, financial ROI, and total value realization . Develop a deep understanding of our customers’ businesses through financial research, on-site collaboration, and cross-functional partnerships . Produce outstanding value scale materials, including vertical assets, self-serve tools, and industry benchmarks . Enable Sales, Solutions, and Customer Success teams by building enablement programs and thought leadership assets . Collaborate within a friendly, entrepreneurial Business Value team backed by highly engaged sales partners . About you Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making . Brings 5–7 years of experience in Silicon Valley technology (preferably within Business Value) or a top-tier consulting firm . Demonstrates curiosity about all types of businesses and industries to seamlessly speak the language of your customer . Proven track record of building and managing collaborative relationships and workloads with Sales reps and leaders . Skilled in financial research, analysis, and building quantitative financial models . Strong track record of establishing t rust and building relationships with senior customer executives . Experience collaborating cross-functionally across multiple SaaS functions (Sales, Solution s, Customer Success, Marketing, Product) . At Asana, we're committed to building teams th at include a variety of backgrounds, perspectives, and skill s, as this is critical to helping us achieve our mission . If you're interested in this role and don't meet every listed requirement, we still encourage you to apply . What we’ll offer Our compreh ensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission . We believe that compen sation should be reflective of t he value you create relative to the market value of your role . To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit . For this role, the estimated "On Target" (fixed and varia ble) range is between $240,000 - $255,000 . The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process . The listed range above is a guideline, and the base salary range for this role may be modified . In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits . If you're interviewing for this r ole, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role . We strive to provide equitable and competitive benefits packages that support our employees worldwide an d include : Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations . If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role . About us Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong. We believe in supporting people to do their best work and thrive. Our goal is to ensure that Asana upholds an environment where all people feel that they are respected and valued, whether they are applying for an open position or working at the company. We provide equal employment opportunities to all applicants without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law. Join Asana’s Talent Network to stay up to date on job opportunities and life at Asana.

Location: Brussels; Rome; Barcelona; Zug; Porto; Cape Town; Istanbul; Eindhoven; Geneva; Milan; Amsterdam; Manama; Madrid; London; Dubai; Berlin; Antwerp; Copenhagen; Vienna; Prague; Athens; Budapest; Paris; Frankfurt; Dublin; Warsaw; Sofia; Luxembourg; Remote; Zurich; Abu Dhabi; Lisbon; Tallinn; London OR Brussels; Seychelles; Rotterdam; Krakow; Johannesburg; Zagreb SENIOR DATA ENGINEER ABOUT KEYROCK Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation. Today, we partner with over 250 team members around the world. Our diverse team hails from 42 nationalities, with backgrounds ranging from self-taught DeFi natives to PhDs. Predominantly remote, we have hubs in London, Brussels, and Singapore, and host regular online and offline hangouts to keep the crew tight. We are trading on more than 80 trading venues, and working with a wide array of asset issuers. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks. But we’re more than a service provider. We’re an initiator. We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. We upgrade ecosystems by injecting liquidity into promising DeFi, RWA, and NFT protocols. And we push the industry's progress with our research and governance initiatives. At Keyrock, we're not just envisioning the future of digital assets. We're actively building it. ABOUT THE TEAM AND WHY THE ROLE EXISTS The Central Data Team (CDT) is only a few months old, but data has been Keyrock's lifeblood since day one. We're now building the Keyrock Data Platform to give Keyrockers, and the AI agents working alongside them, the data and context they need to act fast and autonomously within agreed boundaries and aligned with our shared goals. Doing that means taking data from across the company and making sense of it in real time for all the functions that depend on it: trading desks, wealth and asset management, product, risk, finance, compliance, and research to name a few. You'd be one of the early hires in CDT and we expect you to contribute to most of the bigger decisions and build work. The standards we settle on and the way the team ends up working are still open. WHAT YOU’LL DO - Build streaming and batch pipelines that ingest, normalise, and distribute market, trading, and portfolio data, resilient to feed and exchange failures. - Build the self-serve tooling (SDKs, patterns, templates, AI agents) so other teams publish, consume, and build on data products without waiting on us. - Own data contracts and schema evolution. Keep schema changes from turning into multi-team coordination events. - Design the lakehouse and time-series layer around consumer query patterns. - Build and evolve the Data Governance and Data Quality Framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, self-healing. - Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, performance for wealth and asset management. - Make observability, cost, and performance first-class from day one. - Treat infrastructure as code (Docker, Terraform, CI/CD) alongside our Central Infrastructure Team. - Work in the open: write things down, partner closely with Architecture, Infrastructure, Platform, and the rest of the teams. WHAT WE’RE LOOKING FOR Tools matter less to us than how you think about problems. That said, here's the shape of the person we have in mind. Engineering Craft - 8+ years of building production data systems that other people rely on. - Strong proficiency in Python and SQL: not just being able to write a query, but being able to reason about what the engine is doing with it. - Code that's easy for someone else to read, test, and delete later. - Strong understanding of data modelling for both streaming and analytical workloads. - Efficiency, quality, idempotency, and observability are taken seriously by default. Systems Design - You've designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and you have opinions about partitioning, consumer groups, offsets, and schema registries. - You've used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar are fine too) and can talk about table design as a function of query patterns. - You've worked with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost. - You build for self-healing and idempotency. Reprocessing is safe, retries don't double-write, and the system recovers without a human in the loop. Operational Readiness - Docker, Terraform, and CI/CD are how you work, not a separate "DevOps" thing. - You think about cost and performance early. - You instrument as you build: logs, metrics, and traces are part of the system from day one. - You design for data quality and governance up front covering contracts, validation, lineage, and ownership How You Think and Work - You reason from first principles when a problem is new, stay pragmatic when it isn't, and update your view when you learn more. - You treat the trading desks, wealth and asset management, product, risk, finance, compliance, and research as customers of what you build, and communicate with them that way. - You optimise for outcomes over output. A smaller, simpler thing that ships and works beats a bigger thing that doesn't. - You take ownership end-to-end: design, ship, operate, improve. - You say what you think including when it's an unpopular take. You change your mind when the argument is better. - You make the people around you better. Reviews are real, juniors grow from working with you, and peers want to work with you again. - You're curious about how markets work. Data engineering on its own won't keep you interested here. - You're honest about what you know and what you don't, and quick to close the gap. - You understand financial market data: order books, trades, reference data, portfolios, exposures. Crypto, TradFi, or both are a strong plus. NICE TO HAVE - Lakehouse experience with Apache Iceberg or Delta Lake. - Familiarity with DataHub or similar metadata/lineage platforms. - Rust. Some of our performance-critical services are written in it. Interest is welcome; fluency isn't required. WHAT YOU’LL GET - A from-scratch mandate. You'll be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us. - Strong partners. Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves. You won't be building data in a vacuum. - Autonomy on how you work. Flexible hours, remote-first, business-hours on-call shared across the team. - A competitive salary package, with various benefits. - A team that likes each other. Regular online get-togethers and a yearly onsite where everyone's in the same room. OUR RECRUITMENT PROCESS We’re after those with the right skills and a conscious choice to join our field. The perfect fit? Someone who’s driven, collaborative, acts with ownership and delivers solid, scalable outcomes. As an employer we are committed to building a positive and collaborative work environment. We welcome employees of all backgrounds, and hire, reward and promote entirely based on merit and performance. Due to the nature of our business and external requirements, we perform background checks on all potential employees, passing which is a prerequisite to join Keyrock

Location: Europe Workplace: Remote Asymmetric Research: Asymmetric Research is a specialized security firm focused on long-term, integrated partnerships with L1/L2 blockchains and DeFi protocols. We help teams build resilient systems, strengthen security posture, and proactively address emerging threats. Culture: AR is a fully remote organization and members of our team have been strongly committed to open-source values for decades, having worked at organizations with deep open-source roots and strong security programs including Google, Netflix, Mozilla, Stripe, and Jump Crypto. We pride ourselves on maintaining the highest levels of confidentiality, trust, and professionalism. About the Role: We are looking for a Site Reliability Engineer to join Asymmetric Research. In this role, you will design, operate, and scale mission-critical blockchain infrastructure supporting leading L1/L2 networks and DeFi protocols, working within a high-trust team to deliver secure, highly available, production-grade systems while driving automation, reliability, and operational excellence across our globally distributed environments. Responsibilities: - Manage and maintain a globally distributed blockchain infrastructure fleet - Design, architect, deploy, and operate production-grade infrastructure services - Implement and maintain infrastructure-as-code across development, staging, and production environments - Ensure high availability and performance of mission-critical systems - Contribute to automation, CI/CD pipelines, and operational tooling - Monitor system health and respond to incidents with strong troubleshooting fundamentals - Uphold the highest standards of integrity, professionalism, and operational discipline What we're looking for: - 2+ years of experience in a Site Reliability, DevOps, or Infrastructure Engineering role - Strong experience managing Linux systems and network infrastructure - Hands-on experience with load balancers and high-availability technologies (e.g., HAProxy, ALB/ELB) - Experience with configuration management tools (e.g., Ansible, Chef, Puppet, SaltStack) - Solid troubleshooting skills across hardware, networking, and software systems - Development experience in Go, Python, or Rust - Experience building and maintaining CI/CD pipelines and automated deployment workflows - Experience with open-source monitoring and observability tools (e.g., Grafana, Loki, Prometheus, Alertmanager) Good to have, not required: - Experience operating distributed systems using tools such as Nomad or Kubernetes - Familiarity with blockchain infrastructure, including Bitcoin, Ethereum, Solana, Cosmos, or Move-based ecosystems Benefits: - 25+ days of paid time off - Comprehensive stipends for home office, wellbeing, professional development, and more - Pension/401(k) programs - Life insurance - Premium healthcare - Competitive base salary - Lucrative bonus programs

Location: Canada; San Francisco; United States; New York; Ottawa; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! WHY THIS ROLE? This role is for a highly experienced Back-End Software Engineer who wants to work on core systems that shape how the platform (Model Vault) operates. You will help define the architecture of the platform where reliability, security, performance, and simplicity all matter, and where many of the problems do not have off-the-shelf solutions. Model Vault is Cohere’s inference platform for deploying and operating models securely at enterprise scale. The team owns the systems between a customer and the underlying AI infrastructure, including identity, deployments, metering, billing, security, privacy, and confidential computing. We are strengthening these systems as Model Vault grows, with the goal of scaling to millions of users and supporting some of the world’s most demanding enterprise workloads. AS A SENIOR/STAFF SOFTWARE ENGINEER, YOU WILL: - Evolve and scale the backend systems that power Model Vault, including authentication and authorization, deployment management, billing, metering, and customer lifecycle. - Lead major architectural initiatives across identity, payments, usage systems, platform scalability, and other core product foundations. - Build highly reliable control-plane services for provisioning, configuring, scaling, and operating model deployments across clouds and hardware platforms. - Design APIs and distributed systems with strong guarantees around correctness, consistency, isolation, failure recovery, idempotency, and observability. - Build security and privacy into the platform architecture, including tenant isolation, least-privilege access, auditability, secrets management, encryption, and confidential computing boundaries. - Solve complex problems that span backend systems, cloud infrastructure, security, and AI inference, where conventional SaaS patterns are often not enough. - Drive projects end-to-end, from architecture and threat modeling through implementation, rollout, production operations, and iteration based on real customer workloads. YOU MAY BE A GOOD FIT IF: - You are a strong backend engineer with excellent fundamentals in distributed systems, databases, networking, operating systems, and security. - You have strong programming fundamentals and experience building production systems in languages such as Go, Python, Java, C++, Rust, or similar. You write clean, maintainable, well-tested code and make thoughtful tradeoffs between simplicity, performance, and correctness. - You have designed and operated production systems where correctness, availability, security, and performance mattered at significant scale. - You can take ambiguous, high-impact technical problems, define the right architecture, and drive them through to reliable production systems. - You have strong systems-design instincts and understand concepts such as concurrency, consistency, caching, queues, rate limiting, backpressure, failure domains, idempotency, and graceful degradation. - You think deeply about security boundaries and understand authentication, authorization, identity, cryptography, secrets, tenant isolation, and how small implementation choices can create significant security risks. - You are comfortable reasoning across backend services, APIs, databases, distributed systems, and the cloud infrastructure they run on. - You are comfortable diving into unfamiliar codebases and debugging complex problems that cross service or system boundaries. - You care about the details of production engineering, including instrumentation, capacity planning, migrations, backwards compatibility, incident response, and safe rollouts. - You are comfortable challenging existing architecture and evolving foundational components when the system’s needs change. - You have a track record of taking technically difficult projects from an unclear starting point to systems that other engineers and customers depend on. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

-Развитие существующих backend-сервисов. -Разработка новых сервисов для внутренней инфраструктуры.

Location: Москва Команда занимается сбором качественных данных, которые принципиально важны для обучения передовых моделей ИИ. Обязанности * Определять техническую стратегию и целевую архитектуру системы. * Проектировать системы, готовые к масштабированию от миллионов до миллиардов сущностей: горизонтальное масштабирование, шардирование, геораспределение. * Принимать ключевые технологические решения: выбор стека, стратегии хранения, архитектурные паттерны (event-driven, CQRS и др.). * Проектировать end-to-end пайплайны: URL discovery → fetch → parse → deduplicate → store → deliver. * Писать код самых сложных и критичных компонентов: планировщик обхода, URL-фронтир, дедупликация, проводить performance engineering: профилирование, нагрузочное тестирование, устранение bottleneck-ов. * Оптимизировать прокси-инфраструктуру и маршрутизацию трафика на глобальном уровне, исследовать и внедрять новые технологии: HTTP/3, QUIC, eBPF, io\_uring для максимизации throughput, разрабатывать стратегии оптимизации стоимости инфраструктуры (FinOps). * Руководить командой из 3–6 инженеров: планирование, декомпозиция, приоритизация, формировать и поддерживать технические стандарты: Code Review, coding guidelines, архитектурные ADR, менторить разработчиков, проводить 1-1, помогать в профессиональном развитии, взаимодействовать с потребителями данных и смежными командами для планирования roadmap. Требования * **Знание Python и Go.** * Коммерческий опыт разработки на Python и Go от 7 лет, из них не менее 2 лет в роли техлида/тимлида. * Экспертиза в проектировании распределённых высоконагруженных систем (миллионы RPS, петабайты данных). * Глубокое понимание сетевого стека: TCP/UDP, HTTP/1.1/2/3, TLS, DNS, QUIC. * Практический опыт построения масштабных систем краулинга или аналогичных data acquisition систем. * Экспертиза в асинхронном и параллельном программировании. * Опыт проектирования микросервисной и event-driven архитектуры. * Опыт работы с Kafka, Redis, PostgreSQL, ClickHouse (или аналогами). * Уверенное владение Kubernetes, Docker, Terraform, CI/CD. * Опыт работы с облачными платформами. * Навыки глубокого troubleshooting: tcpdump, strace, perf, eBPF-инструменты. * Опыт управления командой: планирование, Code Review, менторинг, 1-1, найм. Будет плюсом ------------ * Знание Rust или C++ для написания высокопроизводительных компонентов. * Опыт работы в компаниях с масштабным краулингом (поисковые системы, data aggregators). * Опыт работы с io\_uring, eBPF, zero-copy networking. * Опыт построения геораспределённых систем. * Опыт применения ML для оптимизации crawl-стратегий (приоритизация, фильтрация, классификация). * Публичные выступления, статьи. Условия * Крупнейшее DS\\&AI community — более 600 DS-специалистов банка. * Дайджест о самых последних разработках в области DS\\&AI и отчеты с крупнейших конференций мира. * Возможность быть соавтором НИРов и статей для международных конференций. * Возможность выбрать удобный формат работы: гибрид или офис. * Ежегодный пересмотр зарплаты, годовая премия. * Корпоративный спортзал и зоны отдыха. * Более 400 образовательных программ СберУниверситета для профессионального и карьерного развития. * Расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа. * Бесплатная подписка СберПрайм, скидки на продукты компаний-партнеров. * Вознаграждение за рекомендацию друзей в команду Сбера.

Location: San Francisco Workplace: Hybrid ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE Container runtimes were designed for general-purpose software workloads. AI inference is not a general-purpose workload. Running large models at production scale exposes cracks in every layer of the container stack: runtimes unaware of GPU memory constraints, images that take minutes to pull when a model needs to scale to thousands of replicas, and isolation mechanisms that weren’t designed for the multi-tenant serving environments that production AI requires. The tools the industry has relied on for a decade weren’t built for this, and patching around those limitations at higher layers only goes so far. Baseten owns the entire pipeline, from the moment a developer pushes a model to the moment a request gets a response. That vertical ownership means we can fix these problems at the root. The Runtime Fabric team is doing exactly that: purpose-building the container runtime and storage layers for AI inference workloads, led by some of the world’s top containerd maintainers. As Engineering Manager for Storage Products on the Runtime Fabric team, you will lead the engineers who build and run the storage products behind that stack: the Baseten Delivery Network (BDN), which sits in the cold start path of every model on the platform, the snapshotters and filesystems that expose model weights and container images to a running container, and the storage that model deployment and training need next. The team is advancing the next generation of caching for inference workloads, from the origin tier to the GPU host. You will own reliability for the area as a measured outcome, report to the head of Runtime Fabric, and stay close to the code through design and code review. If you’ve managed systems engineers and have hands-on experience with caching, content-addressable storage, or distributed filesystems, we’d love to talk. EXAMPLE INITIATIVES - How the Baseten Delivery Network (BDN) makes cold starts fast https://www.baseten.co/blog/how-the-baseten-delivery-network-bdn-makes-cold-starts-fast/ - Extending BDN from model weights to container image layers, training checkpoints, and deployment artifacts - Lazy-loading snapshotters and block-level delivery (EROFS, FUSE, ublk) so a container can start before the full image or model has arrived RESPONSIBILITIES Team Leadership and Culture - Hire and grow a team of 5 to 10 systems engineers with storage, caching, and Linux expertise - Run the team’s planning and delivery: scope work against the Runtime Fabric roadmap, set priorities, and ship on a predictable cadence - Provide regular coaching, feedback, and career development support to your direct reports - Own on-call health for the team’s services, including escalation paths and follow-through on incidents Technical Direction - Guide the architecture and evolution of the Baseten Delivery Network: the tiered caching and weight delivery product that makes cold starts 2-3x faster and eliminates thundering herd failures during burst scaling events - Shape storage products tailored to Baseten’s workloads: extend BDN from model weights to container images, training checkpoints, and deployment artifacts, and define the interfaces that model deployment, training, and customers use to reach them - Oversee the on-host side of delivery: lazy-loading snapshotters, EROFS and overlayfs layouts, and block-level delivery (FUSE, ublk) for multi-gigabyte files - Own reliability of the delivery path as a measured outcome: end-to-end instrumentation from snapshotter initialization to first inference request, targets for cold start and cache behavior, tolerance for failing upstream registries and object stores, and safe rollout of changes to a path every customer depends on - Make the delivery path work across heterogeneous clusters and cloud providers, each with its own object store and network - Review designs and code across the area, and take on hands-on work where it unblocks the team - Champion the team’s contributions back to containerd and the snapshotter ecosystem alongside the maintainers on the Runtime Fabric team Cross-Functional Partnership - Act as the point of contact for storage across Baseten, ensuring model deployment, training, and platform teams have the integration support they need - Optimize requirements for the underlying storage platforms with the infrastructure team: object storage, local NVMe and block storage, and network bandwidth per cluster, so that capacity and provider decisions account for what the delivery path needs - Manage the team’s dependencies in both directions: sequence work that model deployment, training, and infrastructure teams block on, and negotiate interfaces and timelines with the teams and upstream projects the storage path depends on - Work with the head of Runtime Fabric and product stakeholders to prioritize storage investments based on customer impact and infrastructure reliability - Communicate team progress, technical trade-offs, and incidents clearly to the team and to leadership REQUIREMENTS - Experience managing a team of engineers in a systems, infrastructure, or storage context, including hiring and performance management - Hands-on background in distributed storage systems, content-addressable storage, or large-scale caching infrastructure - Strong systems programming background in Go, Rust, and/or C/C++, with the ability to engage credibly in code reviews and architectural discussions - Working knowledge of the Linux storage stack: filesystems, the page cache, block devices, and mounts - Understanding of how container images are structured, stored, and delivered at scale - Strong written and verbal communication skills, with the ability to influence without authority across teams NICE TO HAVE - Contributions to containerd/containerd, snapshotter projects (stargz, soci, nydus, overlaybd), distribution/distribution, or closely related open-source projects - Familiarity with lazy-loading snapshotters or peer-to-peer image distribution - Experience with EROFS, FUSE, ublk, or io_uring - Experience building or operating CDN, object storage, or large-scale caching infrastructure - Experience running storage services on Kubernetes BENEFITS - Competitive compensation, including meaningful equity - (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!) - Paid parental leave - Fertility and family-building stipend through Carrot - (U.S. only) Company-facilitated 401(k) - Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities. Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you. At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status. We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).

Поддержка и развитие CI/CD пайплайнов (GitLab CI - основной, Jenkins). Миграция и деплой приложений в Kubernetes.

Задачи: — Установление и поддержание отношений с разработчиками и техническим сообществом. — Создание контента (технические статьи, руководства, видеоуроки) для привлечения разработчиков к нашей платформе. — Проведение вебинаров, хакатонов и других мероприятий для продвижения технологий компании. — Участие в технических конференциях, выступления с презентациями. — Помощь разработчикам в интеграции и использовании нашего API/SDK. — Сбор обратной связи от сообщества для улучшения наших продуктов. — Работа в тесной связи с командами маркетинга, разработки и продуктового менеджмента. Требования: — Опыт работы с блокчейн-технологиями и понимание принципов децентрализованных систем. — Умение писать качественные технические материалы (руководства, документацию, статьи). — Отличные коммуникативные навыки, как устные, так и письменные. — Опыт проведения технических мероприятий (вебинары, воркшопы, хакатоны). — Знание хотя бы одного языка программирования (например, JavaScript, Python, Rust, или Solidity). — Уровень английского языка: Upper-Intermediate и выше. Условия: — Конкурентоспособную заработную плату от $4800 до $7000 в месяц, в зависимости от опыта и квалификации. — Возможность работать в инновационной блокчейн-компании. — Полностью удалённый формат работы и гибкий график.

Location: Stockholm ABOUT US: AI NEEDS A NEW INFRASTRUCTURE LAYER. WE'RE BUILDING IT AT MODAL. Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now. Our customers include category-defining companies like Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale. We've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation. Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. THE ROLE: We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform. Specifically, you’ll be working on the distributed object storage system that underpins every container image, volume, and checkpoint on Modal: hundreds of petabytes of data, replicated across multiple cloud object stores and a CDN, cached on local NVMe across a large fleet of workers in many datacenters, and shared peer-to-peer within each datacenter. You’ll make cold starts feel local when the data is hundreds of milliseconds away, designing the caching, preloading, and peer-to-peer layers that hide object-store latency and keep public ingress off saturated uplinks. You’ll own durability and cost at petabyte scale, from streaming and batch replication between origins to garbage collection over billions of objects. You’ll work across the stack, from local disk and page cache to distributed blob storage and garbage collection, and you’ll help shape what storage becomes next as we push storage closer to workloads. WHAT YOU’LL WORK ON: - Build P2P sharing of data across workers within a single datacenter to dramatically reduce ingress - Replicate data across multiple blob storage providers - Automate garbage collection across hundreds of petabytes of data - Deploy colocated storage clusters to datacenters to accelerate high-throughput customer workloads YOU MAY BE A FIT IF: - You have 5+ years of experience writing high-quality production code - You’ve built high-performance distributed storage or caching systems at a large scale (the more challenges you’ve worked through, the better) - You have strong cloud skills, including deep familiarity with object storage (S3 or similar), CDNs, and their consistency, throughput, and cost characteristics - You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, page cache, containers, etc.) - You’re willing to step into the thick of it with our on-call rotation and respond to production incidents NICE-TO-HAVE: - Experience with replication, content addressing, and consistency models in multi-region or multi-cloud systems - Experience operating storage systems at scale (petabyte-scale datasets, high-throughput read/write paths, large-scale garbage collection or data migration) - Experience with data engineering at petabyte scale - Prior experience with Rust

Location: London, United Kingdom - Deliveroo Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. About the Role Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. In November 2023 we launched our non-food retail offering, Deliveroo ‘Shopping’, where we work with large and small merchants. We oversee all operations within the grocery and retail ecosystem, ensuring stores are equipped to receive and efficiently process orders. Our solutions empower stores to manage orders seamlessly through multiple channels, including our in-house app, API integration, and devices pre-installed with our software. Additionally, we provide tools to maintain and update product catalogs, ensuring accurate inventory for consumers. The technology we’ve developed enables our partners to pick the correct items swiftly while keeping inventory data current, optimizing both efficiency and accuracy. We’re looking for a Staff Software Engineer to join our London, UK - Hybrid (3 days from the office) team. In this role, you’ll help us define technical solutions for critical business problems and lead the technical direction for complex, high-scale systems. Get to know our Engineering team — what drives us, how we work, and what you can expect. What You’ll Be Doing You’ll be joining a high-impact engineering group focused on solving unstructured and ambiguous challenges. You will act as a technical authority, aligning non-adjacent teams to deliver results that move the needle for the entire organisation. Here’s what your day-to-day might look like: Drive Technical Excellence: Improve code structure and architecture across your team’s remit, developing, releasing and running large-scale web applications whilst transitioning our monolithic codebase to a microservice-based architecture Lead Project Planning: Foresee dependencies and risks, partnering closely with Product and Design to ensure smooth delivery of complex features, whilst defining the backend architecture and tech stack for a product area Optimise Operations: Improve performance, reliability, scalability and security for our backend systems Collaborate & Influence: Build relationships across global engineering teams to identify collaboration opportunities and influence the wider technical roadmap. Mentor & Hire: Support the personal growth of your colleagues through technical guidance and take an active role in conducting engineering interviews to scale our team. What You’ll Need to Thrive Our ideal candidate will bring strong expertise in some of these areas and curiosity to grow in others: Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Strong Engineering Principles: Deep pride in writing readable, well-designed, and well-tested software. Backend Expertise: Significant experience building web-based applications (we use Go, Ruby/Rails, Python, Scala, and Rust). Data Proficiency: Practical experience with relational databases (PostgreSQL, MySQL) and "NoSQL" backends like Redis, DynamoDB, or ElasticSearch. Systems at Scale: Proven ability to manage web architecture at scale (handling 20krpm and above). Technical Leadership: Experience breaking down large pieces of work and guiding implementation choices for a team of engineers. Why Join Us? At Deliveroo, you’ll do work that matters—solving real-world problems in a three-sided marketplace that’s constantly evolving. We’re food lovers, problem solvers, community organisers, proud parents, and more, brought together by a shared drive to make things better. Working here you can expect to: 🔧 Solve meaningful problems at real scale Work on a complex, always-on marketplace that impacts millions every day. 🌱 See your impact, fast Ship, test and improve ideas quickly in a low-hierarchy, high-ownership environment. 🧠 Grow through challenge and ownership Take on big, ambiguous problems and accelerate your career with strong support. 🌎 A culture built for builders High standards, collaboration, flexible working and continuous learning. ​​💰 Share in the success you help create Competitive salary and equity options, so you’re rewarded for the impact you make. Diversity, Equity and Inclusion At Deliveroo, we know that a great workplace reflects the world around us and that true diversity and inclusion make us stronger, more creative, and better at what we do. We’re committed to fostering an environment where everyone can do their best work and feel they belong. We believe in equality of opportunity and welcome candidates from all backgrounds regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion, or belief. If you have a disability or long-term health condition and need support to apply for one of our roles, or require any reasonable adjustments during the recruitment process, you’ll have the opportunity to let us know once you’ve submitted your application. We’ll share details on how to request support so we can ensure you have a fair and equitable experience. If you’re excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we’d love to hear from you! Beware of recruitment scams: DASH Brands will never ask you to pay money or share sensitive financial information during hiring — learn more about DASH Brands' legitimate recruiting process at careersatdoordash.com/recruitment-scam-awareness .

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker is looking for a Senior Software Engineer to build AI-powered developer tools and the platform behind them on our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building tools that make Docker's engineers more productive and the platform that lets teams across Docker prototype, deploy, and scale their own AI developer tools. As a Senior Engineer you will design, build, and operate: - AI-Powered Developer Tools. AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. - Self-Service AI Developer Tools Platform. Platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools, using the patterns and standards the team sets. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal and Staff engineers, product engineering teams, and platform teams across Docker. _______________________________________________________________________ WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a strong, hands-on engineer who enjoys building at the intersection of AI, developer experience, and platform engineering. You have built software on top of LLMs and AI agents and have a good sense of what works in practice. You care about the people using your tools, and you can tell a tool developers love from one they put up with. You take a feature from a vague request to production: you ask the right questions about requirements, design it sensibly, ship it iteratively, and operate it afterward. You are comfortable in a fast-moving AI landscape and balance quality with pragmatism. You make the engineers around you better through thoughtful code review and by sharing what you learn. _______________________________________________________________________ RESPONSIBILITIES BUILDING AND OPERATING AI DEVELOPER TOOLS - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Integrate LLM providers, agent orchestration frameworks, and MCP servers into reliable tools, following the team's patterns and standards - Build systems that help Docker's engineers adopt AI-native development tools - Build integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Instrument your tools so the team can measure adoption, effectiveness, and developer satisfaction SELF-SERVICE PLATFORM - Build and improve platform capabilities, including deployment pipelines (ArgoCD/GitOps), observability integration (Grafana), security controls, and cost management, that help teams ship their own AI tools faster - Help reduce time-to-production for new products from weeks to days - Contribute to reliability, security, and performance standards for AI systems, including SLOs, monitoring, and incident response DESIGN AND DELIVERY - Take features and services from requirements to production. Ask about scale, users, and constraints before designing, and write down your assumptions - Write clear design documents for the work you own, and participate in design reviews for the team - Review code thoroughly and share what you learn with the rest of the team - Take part in the team's on-call rotation, and help improve alerts, runbooks, and tooling so the next incident is easier - Follow the AI-assisted engineering practices the team sets: use AI tools critically, validate their output, and stay accountable for what you ship COLLABORATION AND GROWTH - Work with the Senior Manager and the team's Principal and Staff engineers to understand priorities and shape your work - Partner with Infrastructure, Security, and Data teams on integrations and shared standards - Help newer engineers get up to speed on the team's tools, patterns, and practices - Keep up with emerging AI/LLM technologies and agent frameworks, and bring useful findings back to the team _______________________________________________________________________ QUALIFICATIONS REQUIRED - 6+ years of software engineering experience building and operating production systems - Hands-on experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Working knowledge of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Experience building and operating scalable backend services, distributed systems, or developer-facing platforms - Experience with cloud-native infrastructure, including Kubernetes, CI/CD pipelines, and observability systems - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience building developer tools, platform systems, or internal tools that other engineers rely on - Good product judgment: you weigh developer experience and technical trade-offs, and you ask clarifying questions before committing to a design - Clear written and spoken communication suited to a remote, async-first company - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Comfortable working autonomously in a distributed, remote-first team - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience with GitOps deployment patterns (ArgoCD) or Grafana-based observability - Familiarity with security and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) _______________________________________________________________________ WHAT TO EXPECT FIRST 30 DAYS - Learn Docker's current AI and developer tooling landscape, the team's services, and the architecture decisions made so far - Meet your teammates, including the Principal and Staff engineers, the Senior Manager, and key stakeholders in product engineering - Ship a useful production change in your first weeks, using the team's AI-assisted engineering workflow - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Shadow on-call and learn the operational profile of the team's services FIRST 90 DAYS - Own a feature or service from design to production with measurable impact, such as part of an AI code review agent, a deployment diagnostic agent, or an on-call assistant - Write the design document for work you own and take part in team design reviews - Contribute to the self-service platform's deployment pipeline, observability integration, or security controls - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be a go-to engineer for one or more of the team's AI tools or platform components - Have shipped multiple production improvements that Docker engineers use every day, with adoption and effectiveness you can point to - Have helped teams outside AI Developer Tools build and run their own tools on the platform - Have taken on larger and more ambiguous work as your scope grows, and helped newer engineers do the same Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $160,900 – $260,700 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE

Location: San Francisco, CA; Seattle, WA Workplace: Remote ABOUT DOCKER Docker has been one of the most loved brands in developer tooling, trusted by more than 20 million monthly users and over 20 billion container image pulls. From solo founders to the world's largest companies, developers rely on Docker to build, share, and run their applications across our suite of products including Docker Desktop, Docker Hub, and Docker Scout. We are a globally distributed, remote-first team building the tools that define how software gets built and delivered. As AI agents redefine software development, Docker is at the center of that shift, providing the sandboxed environments, verified images, and secure infrastructure that make autonomous workflows trustworthy by default. _______________________________________________________________________ THE ROLE Docker is looking for a Staff Software Engineer to set the technical direction for key parts of our AI Developer Tools team. You will work at the intersection of AI, developer experience, and platform engineering, building the AI-powered tools and the platform that let teams across Docker prototype, deploy, and scale their own AI developer tools. As a Staff Engineer you will own the technical design and delivery for two areas: - AI-Powered Developer Tools. Design and build AI agents and tools that accelerate developer productivity, surface observability insights, and automate operational reviews. You will help teams adopt an AI-native way of working and speed up adoption of tools such as Claude Code and Codex. Examples include AI-powered code review and refactoring assistants, automated test generators and local environment setup tools, deployment pipeline diagnostic agents, and agents that simplify on-call work during incidents. - Self-Service AI Developer Tools Platform. Design and build the platform infrastructure that lets product and platform teams across Docker unblock themselves by prototyping, building, and deploying their own AI developer tools. You will set the patterns and standards that let teams experiment, iterate quickly, and graduate successful prototypes into production-ready services. You will report to the Senior Manager, AI Developer Tools, and work closely with the team's Principal engineers, engineering leadership, product engineering teams, and platform teams across Docker. _______________________________________________________________________ WHAT WOULD MAKE SOMEONE SUCCESSFUL IN THIS ROLE You are a hands-on technical leader who works well at the intersection of AI, developer experience, and platform engineering. You have shipped production systems built on LLMs and AI agents, and you can explain what worked and what did not. You think in platforms: you design something once so that several teams can move faster. You have clear opinions about what makes a developer tool good, and sound judgment about when to build, when to integrate, and when not to do either. You are comfortable in a fast-moving AI landscape and balance technical quality with shipping iteratively. Before you design, you ask about scale, users, and constraints rather than assuming them. You lead through influence and mentorship, and the engineers around you get better because you are on the team. _______________________________________________________________________ RESPONSIBILITIES TECHNICAL LEADERSHIP AND ARCHITECTURE - Set technical direction and own the architecture for AI-powered developer tools and the self-service platform within the team's roadmap - Turn ambiguous problems into clear requirements, plans, and staged decisions. Ask about scale, users, and constraints before designing, and write down your assumptions - Establish patterns, standards, and best practices for LLM integration, agent development, and production AI systems that the team and partner teams adopt - Shape platform capabilities including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, and operational tooling for AI developer tools - Design reliable, scalable infrastructure for hosting AI agents and developer tools - Recommend AI technology choices, LLM provider strategies, and agent orchestration approaches, and make the trade-offs explicit - Work with the Senior Manager and the team's Principal engineers to align technical decisions with business goals SYSTEMS DESIGN AND IMPLEMENTATION - Design, build, and operate production AI agents for developer productivity, including code review assistants, test generators, deployment diagnostics, and incident response automation - Build self-service platform capabilities that reduce time-to-production for new AI tools from weeks to days - Build systems that speed up adoption of AI-native development tools (Claude Code, Codex) across Docker's engineering organization - Set and meet reliability, security, and performance standards for AI systems, including SLOs, monitoring, incident response, and cost management - Design integrations between AI developer tools and existing developer infrastructure such as CI/CD pipelines, observability platforms, and deployment systems - Take part in the team's on-call rotation and use what you learn to improve alerts, runbooks, and tooling STRATEGIC IMPACT AND INNOVATION - Evaluate emerging AI/LLM technologies, developer tooling trends, and agent frameworks, and recommend what Docker should adopt and what it should not build - Define how we measure AI tool effectiveness, including adoption, productivity gains, and developer satisfaction - Improve AI tool performance, cost efficiency, and developer experience through architectural improvements - Contribute to the technical approach for hardening proven internal tools so other teams across Docker can adopt them - Lead cross-team technical delivery, surface risks early, and work with Infrastructure, Security, and Data on shared standards LEADERSHIP AND MENTORSHIP - Mentor senior engineers on AI/LLM integration patterns, agent development, and platform engineering practices - Lead design reviews and raise the quality of design and code reviews across the team - Create reusable patterns, documentation, and architectural decision records (ADRs) that other engineers build on - Help the team turn good individual AI-assisted engineering practice into shared workflows and controls - This role may require participation in an on-call rotation to provide support outside of standard business hours, including evenings, weekends, and holidays, as needed. _______________________________________________________________________ QUALIFICATIONS REQUIRED - 8+ years of software engineering experience, with demonstrated technical leadership on production systems at scale - Hands-on production experience building LLM-powered applications, AI agents, or AI-assisted developer tools - Strong understanding of LLM APIs (OpenAI, Anthropic, and others), prompt engineering, agent orchestration frameworks, and practical uses of AI in software development workflows - Track record of designing and building scalable distributed systems and developer-facing platforms - Production experience with cloud-native infrastructure, including Kubernetes, GitOps deployment patterns, observability systems, and CI/CD pipelines - Proficiency in Go (preferred), Rust, Java, or Python, with strong software engineering fundamentals - Experience designing developer tools, platform systems, or internal tools that other teams rely on - Track record of clarifying requirements and constraints with stakeholders before committing to a design - Track record of leading complex initiatives that crossed team boundaries, and of influencing without direct authority - Strong product and platform judgment: you weigh business outcomes, developer experience, and technical trade-offs - Clear written and spoken communication suited to a remote, async-first company - Track record of mentoring other experienced engineers - Ownership mentality with a bias for action and iterative delivery in ambiguous, fast-moving environments - Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience PREFERRED - Experience with MCP (Model Context Protocol) or similar AI agent integration standards - Background in developer productivity, DevOps, SRE, or platform engineering - Contributions to open source AI tools, developer tooling, or platform engineering projects - Experience evolving an internal platform or tool into a widely adopted, production-grade service - Knowledge of security, compliance, and operational practices for production AI systems - Experience with infrastructure-as-code (Terraform, Pulumi) and major cloud platforms (AWS, GCP, Azure) _______________________________________________________________________ WHAT TO EXPECT FIRST 30 DAYS - Build context on Docker's current AI and developer tooling landscape, including existing AI experiments, LLM provider relationships, and architecture decisions to date - Meet the Senior Manager, the team's Principal engineers, engineering leadership, and key stakeholders in product engineering to understand needs, pain points, and constraints - Review existing AI tool prototypes and internal experiments to learn what is working and what is not - Get hands-on with the team's services and ship a useful production change - Shadow on-call and learn the operational profile of the team's services - Work with the Senior Manager to agree on initial technical priorities FIRST 90 DAYS - Lead the technical framing and delivery plan for one significant problem, from requirements through to production - Document the architecture, technology choices, and integration patterns for that work, including ADRs - Ship a production AI developer tool that sets patterns the team can reuse (for example an AI-powered code review agent, a deployment diagnostic agent, or an on-call assistant) - Contribute to the technical foundations of the self-service platform: deployment pipeline, observability integration, security controls, and cost management - Lead design reviews for your area of the roadmap and begin mentoring other engineers - Take part in the on-call rotation FIRST YEAR OUTLOOK - Be the trusted technical lead for your area of AI Developer Tools, and a sought-after partner for teams across Docker - Deliver at least one material outcome that spans multiple teams or systems - Have multiple production AI tools demonstrating value across Docker's engineering organization - Help build a self-service platform that lets multiple teams build, deploy, and operate their own AI tools with little friction - Define and instrument how the team measures AI tool adoption, effectiveness, and developer productivity impact - Grow other senior engineers into broader ownership, and reduce the number of decisions that depend on a small set of people Visa sponsorship: Docker considers visa sponsorship on a case-by-case basis based on business needs. _______________________________________________________________________   COMPENSATION & EQUITY All full-time roles include equity. Final compensation is determined on factors including but not limited to experience, skills, qualifications, and location. United States: $170,350 – $275,550 base ______________________________________________________________________ POSTING INFORMATION - Open vacancy: This posting is for an existing open role. - AI in hiring: Docker may use AI-assisted tools during our recruiting process. - Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations. Recordings are optional and require explicit consent. ______________________________________________________________________ PERKS & BENEFITS - Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration. - Flexibility that fits your life – We trust you to manage your schedule while delivering great work. - Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break. - Home office support – Set up your workspace for comfort and success. - Technology stipend – Equivalent to US$100 net per month to help support your work. - Learning & development – Annual stipend for conferences, courses, certifications, and continued learning. - Parental leave – 16 weeks of paid parental leave after six months of employment. - Equity for all full-time employees – Share in Docker's long-term success as we continue to grow. - Comprehensive benefits – Medical, retirement, and paid holidays vary by country. - Docker swag – Because representing the whale never gets old. Docker is proud to be an equal opportunity employer. We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives. We believe diverse teams build better products, make better decisions, and better serve our global community. #LI-REMOTE