Вакансии

Location: Ukraine; Spain; Slovakia; Serbia; Yerevan; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDE and an FDX,  Forward Deployed Executives (FDX) own the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs. Forward Deployed Engineers (FDE) embed with a client, map the client workflow, identify the business problem underneath it, design and build a working AI solution, present to the client, and transfer the knowledge to the client's team. Owns technical direction of the whole solution. Senior AI Engineer. When an FDE comes back from the client with the business problem, you will help turn that into an agentic system that runs in production and will be responsible for evaluation, observability, and guardrails.  You'll have real ownership of components and of the technical decisions inside them. Requirements: Mindset Proactive and self-directed; you push for clarity rather than waiting for a ticket Excellent communication and problem-solving skills Comfort with ambiguity and ownership. B2+ English, comfortable collaborating across distributed, multicultural teams. Technical depth 5+ years in software or ML engineering, with production systems you were accountable for. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes. Shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks. Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production. Strong engineering fundamentals. Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure. Python and/or TypeScript proficiency; depth matters more than stack. Dropped into an unfamiliar codebase, you're productive. Hands-on AWS in production: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus. Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release. Model and agent monitoring, drift detection. Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs. Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus. MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus. Nice to Have: Experience in one of the industries: financial services, insurance, healthcare. Consulting, professional services, or other embedded customer-facing delivery. AWS and Claude Code Certifications A2A: you can explain agent-to-agent interoperability CI/CD pipeline experience (GitHub Actions, GitLab CI) Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines. Experience in an additional language (Go, TypeScript, or Rust). Experience with Apache Spark, Apache Airflow, Kafkа Responsibilities: Work in a pair with an FDE and an FDX. Build and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Build and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Integrate AI components into backend services and RESTful APIs Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD. Implement LLMOps and AgentOps practices: agent tracing, prompt and version management, cost and latency monitoring, regression testing, drift detection Start from the blueprint, contribute to enablement and handover: clear documentation, runbooks, and pairing with the client engineers who will inherit the system. Feed reusable components and lessons back into the Provectus Blueprints Participate in technical discussions and architectural decisions Conduct model evaluation, improve failure modes you find, optimize model performance, efficiency, and reliability Mentor junior and mid-level AI engineers, conduct code reviews and share knowledge across the team through documentation, presentations, and workshops. What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside FDE and FDX A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: Ukraine; Serbia; Yerevan; Spain; Slovakia; Slovenia; Poland Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: North Macedonia; Montenegro; Moldova; Bulgaria; Czechia; Bosnia and Herzegovina; Croatia Workplace: remote Provectus is an AWS Premier Partner and an Anthropic Strategic Partner , working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements. Where this role sits You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize: Forward Deployed Executive (FDX) owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction. Forward Deployed Engineer (FDE) embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered. What You’ll Do: Take the seat Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow. Build Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer. Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team. Own the outcome. Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number. Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here. Be credible with the customer’s engineers and their executives. Shape what we commit to before we commit to it. What You’ll Bring: Mindset Proactive and self-directed; identify problems before they're handed to you Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job B2+ English, comfortable collaborating across distributed, multicultural teams Client Engagement You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run Technical depth 7+ years building and running production systems. Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks. Experience building and optimizing RAG systems in production Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Experience in making and defending architectural trade-off decisions Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release Model and agent monitoring, drift detection Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs Hands-on production experience with the Claude ecosystem —  Claude Code, CLAUDE.md, hooks, skills files.  Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution Experience in one of the industries: financial services, insurance, healthcare Consulting, professional services, or other embedded customer-facing delivery A2A: you can explain agent-to-agent interoperability AWS and Claude Code Certifications CI/CD pipeline experience (GitHub Actions, GitLab CI) Experience in an additional language (Go, TypeScript, or Rust) Experience with Apache Spark, Apache Airflow, Kafkа What We Offer: The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance Career growth; we actively develop our engineers Access to the latest AI tools and premium subscriptions Long-term B2B collaboration Private medical insurance or a budget for your medical needs Paid sick leave, vacation, and public holidays Equipment and all the tech you need for comfortable, productive work How we hire: Intro conversation. The role, your background and aspirations, tech questions. Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant HR Interview. Soft skills and expectations HM interview. Tech questions; a live engineering session is also possible

Location: New Jersey; New York; Pennsylvania; Connecticut; Massachusetts Workplace: remote About the role: At Provectus, you don’t prototype in a sandbox and hand a client a slide deck. You embed inside a bank, an insurer, or a health system, learn the work, and ship a Claude + AWS system into their real, regulated production — then you watch the business number move. We’re an Anthropic and AWS Partner with 150+ certified architects. That means the newest models, real budgets, and problems that matter — without the layers, politics, and years-to-impact of a hundred-thousand-person firm. 350+ builders, 100+ customers in production, founder-led since 2010, offices across North America, LATAM, and EMEA. Why Provectus Frontier access — Anthropic Preferred Partner: newest Claude models, real budgets, real problems. Real tasks (not scope), real deployment. You go where the operating problem is and ship production code to real users, not slide decks that sit in a drive. Embedded, not engaged. You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Embedded is not staff-augmented. Autonomous. You own the work from framing through to production, visible to clients and founders.  You own the method; nobody hands you a ticket. Your experience stays portable. Every engagement is a new problem, often in a new industry, so your skills compound instead of narrowing to one product. No legacy-maintenance grind, not a single stack. Craft & growth — build beside senior FDEs on a Claude-certified team; a real platform (talks, OSS) to grow your name. We give you a stage: Claude certification, conference talks, open-source contributions, published work under your own name. What we look for: Typically 7+ years building software, a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. Genuinely willing to spend time understanding someone else’s job before writing code; demonstrated ability to become conversant in an unfamiliar business function quickly. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus), including the operational reality of a system someone else inherits. Pre-sales experience. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Hands-on experience with Claude, Claude Code, and Cowork (skills, workflows, MCP, integrations, connectors, custom harnesses). Nice to have Containers and orchestration (Kubernetes/ECS) and CI/CD in production. IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Spend the first weeks of each engagement in the operator’s seat, learning the constraints from the inside, then rebuild the function from first principles alongside the client and a Forward Deployed Executive — and you are the one who builds it. Be part of the customer’s team, inside their process; work on real tasks, not scoped deliverables, and own the method autonomously. You won’t start from zero. Provectus builds industry Blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. Deliver across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare. Help shape how leading enterprises adopt AI, from strategy through first deployment; help build the tooling and frameworks of a growing AI delivery practice. What We Offer: Full-time. On-site visits to client’s facilities and our office in NYC 1/week Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. Base salary $180k–$200k + bonuses; OTE up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, and abilities of the applicant, and alignment with market data. We’re real: A person reads your application. We filter out AI-generated and fraudulent submissions automatically. Every application that clears that filter is read by someone on our team. We may ask for a quick ID verification. Fraudulent applications are common, and this protects real candidates. You’ll meet the people you’d work with. We host AI engineering events in New York and San Francisco. We'd be happy to talk in person. Your interviews are with Pavel Borobov, Solutions Architect, and Stepan Pushkarev, Co-Founder & CEO. How we hire: Recruitment interview. Tech interview with our FDE (30 min). A live engineering building session (1.5 hours). We hand you a business function and the constraints. You have to understand the job and rebuild it — then say what you’d build and how you’d know it worked. Use AI the way you normally would; we expect AI-generated code. What we look at is how you used AI, the judgment behind your choices, and what you researched beyond what any LLM already knows. 4. Soft skills interview. 5. Offer discussion.

Задачи: - Поддерживать текущие алгоритмические решения - Проектировать и внедрять AI-агентов (LLM, GPT-like модели) в различные процессы - Адаптировать и дообучать LLM (например, LLaMA, Mistral, YaLM 2) под специфику продукта - Разрабатывать RAG-пайплайн для поиска и обработки данных - Настраивать векторные БД (Pinecone/Weaviate/Qdrant) и оптимизировать кэширование Требования: - Знание современных AI-фреймворков и библиотек (LangChain, LlamaIndex и других) - Уверенное владение Python и PyTorch/TensorFlow - Практический опыт работы с API, Docker/Kubernetes и базами данных - Опыт внедрения RAG

Location: Munich; Neuss; Berlin Workplace: Hybrid ROLE HIGHLIGHTS: - Role: Forward Deployed AI Engineer - Department: Forward Deployed Engineering - Location: Germany - Reports to: VP, Forward Deployed Engineering - Working type: Hybrid (On-site at customer locations approx. 50% of time) - German security clearance (Sicherheitsüberprüfung Ü1/Ü2/Ü3) - 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: US, Boston, MA Workplace: OnSite Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further. ABOUT THE ROLE We are looking for a Controls Engineer to join our Control Team in Boston. You will own how we know our controls stack works: the testing and validation infrastructure that turns "it looked fine on the robot" into measured, reproducible evaluation, the observability and failure analysis that makes runtime behaviour visible and failures shareable, and the documentation and runbooks that let the team self-serve without institutional knowledge. You will also strongly contribute to first-time bring-up of new hardware for Boston components and validate changes end-to-end on real robots before the wider team depends on them. The ideal candidate has strong control fundamentals, solid software engineering discipline across the stack - from control code to test harnesses to diagnostic tooling - and the debugging instincts that only come from real hardware. You will work across the whole control stack and be the person the team relies on to tell them the truth about their code. WHAT YOU'LL DO Testing & Validation Infrastructure: - Build and own hardware-in-the-loop (HIL) and integration test workflows that quantify controller and motion repeatability and accuracy - turning "it looked fine on the robot" into measured, reproducible evaluation. - Define and implement repeatability and accuracy metrics for controller and motion changes, and the harnesses that make those measurements consistent across runs and across robots. - Expand unit and integration test coverage across the controls components the team actually runs - actuator drivers, hardware interfaces, whole-body control, and the teleoperation pipeline. - Develop automated regression checks that surface controls regressions - in accuracy, repeatability, or behaviour - in simulation and on hardware before they reach the wider team. - Work with controls engineers to define testability requirements for new components and algorithms, so things are built to be evaluated and validated. - Package controllers into cleanly separable, reusable, and easily testable interfaces - so individual controllers can be developed, swapped, and validated in isolation. New Hardware Bring-Up & Integration: - Strongly contribute to first-time bring-up of new hardware for Boston components, and to their integration into the controls stack. - Validate hardware and software changes end-to-end on real robots before broader team use - structured, documented, and repeatable. Debugging, Observability & Failure Analysis: - Instrument the controls stack to improve visibility into runtime behaviour - logging, tracing, and diagnostic tooling. - Reproduce hardware and software failures in structured, developer-shareable formats; feed structured root-cause context back to algorithm and hardware owners. - Identify and resolve cross-stack failure modes that span controls, firmware, and hardware. Documentation & Knowledge Transfer: - Write and maintain engineering documentation for the controls stack: HIL and test coverage, and bring-up/integration guides for new hardware. - Own runbooks that let controls engineers self-serve validation, integration, and recovery without relying on institutional knowledge. WHAT WE'RE LOOKING FOR - Substantial hands-on robotics experience on real hardware. - Strong control theory foundation (joint-space control, PID and feedforward, impedance/admittance, observers, state estimation, filtering, stability) — enough to define meaningful repeatability and accuracy metrics for a control stack and interpret what they say. - Shipped software across the stack: modern C++ inside a real-time control codebase, plus Python for test harnesses, analysis and tooling. - Built test automation, HIL or integration-test infrastructure for complex physical systems — and got other engineers to actually use it. - Solid measurement and data analysis judgement: sampling, timing and synchronisation, noise, statistical significance, and knowing when a difference between two runs is real. - Strong debugging across software/firmware/hardware boundaries, with the discipline to reproduce failures in a form other engineers can act on. Nice to have: - Physics simulation environments (MuJoCo, Isaac Sim/Isaac Lab) and sim-to-real validation. - Observability tooling: logging and tracing frameworks, metrics collection, time-series databases, dashboarding (e.g. Grafana). - First-time hardware bring-up experience: new actuators, sensors or compute targets integrated into a control stack. - A track record of engineering documentation and runbooks that outlived their author. - Release management or quality gates for safety-relevant software. WHAT WE OFFER - Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources. - Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays. - 401(k) retirement plan with 4% employer match. - Competitive equity: stock options with meaningful upside as we scale. - Free daily catered lunch, snacks, and drinks in‑office. - Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics. - Freedom to influence the product and own key initiatives.

Location: New Delhi Workplace: Remote Global Services is the centre of expertise at Chainalysis — the team that translates our platform, data, and investigative capabilities into real-world impact for customers across law enforcement, national security, financial institutions, and the broader crypto ecosystem. Chainalysis is seeking a Deployment Strategist to join Global Services as a core technical practitioner. This is not a traditional services or solutions engineering role. Deployment Strategists are embedded technical experts who own the full lifecycle of customer value — from problem discovery and investigation through solution design, deployment, and customer enablement. The role sits at the intersection of blockchain investigation, data analytics, domain expertise, and customer partnership. You will work directly with customers to understand their mission, conduct investigations, build tailored solutions, and enable customer teams to operationalise Chainalysis independently. Success requires deep investigative capability, genuine domain expertise, technical skill, and the ability to build trusted relationships through credibility — not just communication. This is the role that makes Chainalysis essential to how our customers operate. In this role, you’ll: - Own end-to-end customer engagements — from discovery through investigation, solution design, deployment, enablement, and ongoing value delivery - Conduct blockchain investigations across the Chainalysis platform, applying tracing, OSINT, and analytical techniques to real customer problems - Partner directly with customers to understand investigative, intelligence, compliance, or operational objectives and translate them into actionable outcomes - Design, build, and maintain custom workflows, notebooks, dashboards, queries, and data models using Chainalysis data and products - Enable customers to operate solutions independently — building their capability so that Chainalysis becomes embedded in their operational infrastructure - Act as the primary technical and domain advisor for your customers, building trusted relationships through hands-on expertise and credibility - Deliver live training, demos, investigative walkthroughs, and technical briefings to both technical and non-technical audiences - Support pre-sales technical engagement for complex and strategic deals — helping customers understand what's possible and how to get there - Collaborate closely with Product, Engineering, Global Intel, and Sales to influence roadmap and improve offerings based on field intelligence - Develop and share domain expertise, investigative techniques, and best practices that raise the capability of the wider GS team We’re looking for candidates who have: - Conducted or directly supported cryptocurrency investigations, blockchain intelligence work, or financial crime analysis in an operational environment - Deep familiarity with blockchain ecosystems (BTC, ETH, stablecoins, DeFi) and how on-chain data is used in investigations, compliance, or intelligence workflows - Delivered customer-facing technical solutions — whether investigative outputs, data products, or analytical workflows — in complex, real-world environments - Worked directly with customers in law enforcement, national security, intelligence, compliance, financial crime, or security-focused domains - Built insights from large or complex datasets and communicated findings to varied audiences — from analysts to executives - Operated successfully in fast-paced, ambiguous environments requiring ownership, adaptability, and sound judgment - Excellent English and Hindi Required Technical Skills: - Proficiency in Python and SQL for data analysis, transformation, and solution development - Experience building notebooks, dashboards, and analytical workflows - Solid understanding of data modelling, querying, and working with large datasets - Ability to quickly develop deep expertise in Chainalysis data structures, schemas, and products Domain Expertise - Substantive knowledge of at least one domain: financial and cyber crime investigations, sanctions and compliance, fraud, national security, DeFi/protocol security, tax, or private sector risk - Understanding of how customers in your domain operate — their workflows, regulatory environment, and what success looks like for them - Ability to apply domain knowledge to shape investigation approach, solution design, and customer advisory Nice to have experience: - Direct experience with Chainalysis products - Background in law enforcement, intelligence, or military investigations - Experience providing expert evidence or supporting legal proceedings - Familiarity with compliance frameworks (BSA/AML, sanctions screening, MiCA, Travel Rule) - Experience with data engineering tools and platforms (e.g., Databricks, Snowflake, cloud-based analytics) - Published research, intelligence products, or thought leadership in blockchain analytics or financial crime AI at Chainalysis AI is not a feature at Chainalysis - it is a new way of working. One that turns instructions into work done, and helps us move faster than the threats we're built to counter, and we expect our employees to take ownership of the output and ensure quality. As the world's most trusted blockchain analytics platform, Chainalysis sits at a rare intersection of proprietary data, regulatory relationships and crypto expertise that makes it uniquely placed to shape and lead the next era of AI-driven intelligence - and we expect everyone here, regardless of role, to be an active part of it. AI fluency is tied directly to how we measure performance and how we plan to win. There is no substitute for your own curiosity. We provide the tools, workflows, and space to experiment - but the expectation is that you develop these capabilities yourself, bring ideas, and collaborate across teams to reinvent the way work gets done. We are not using AI to do less. We are using it to do what was never possible before. About Chainalysis Chainalysis is the blockchain data platform, making it easy to connect the movement of digital assets to real-world services. Powered by deep blockchain data and AI, organizations can investigate illicit activity, manage risk exposure, and develop innovative market solutions built on the industry's most trusted blockchain intelligence. Our mission is to build trust in blockchains, blending safety and security with an unwavering commitment to growth and innovation. You belong here.  At Chainalysis, we believe that diversity of experience and thought makes us stronger. With both customers and employees around the world, we are committed to ensuring our team reflects the unique communities around us. We’re ensuring we keep learning by committing to continually revisit and reevaluate our diversity culture. We encourage applicants across any race, ethnicity, gender/gender expression, age, spirituality, ability, experience and more. If you need any accommodations to make our interview process more accessible to you due to a disability, don't hesitate to let us know. You can learn more here https://go.chainalysis.com/rs/503-FAP-074/images/Interview%20Accommodations%20Request.pdf. We can’t wait to meet you.

Задачи: — Проектирование и разработка продвинутых AI-workflows и агентных архитектур — Разработка и оптимизация RAG-пайплайнов — Создание качественных промптов и проведение экспериментов со стратегиями prompt engineering — Работа с LangChain и другими LLMOps-инструментами для оптимизации производительности чат-бота — Анализ поведения пользователей для повышения точности и естественности AI-системы — Тесное взаимодействие с инженерной и продуктовой командами при тестировании и внедрении улучшений — Отслеживание новых тенденций в области LLM и conversational AI — Развитие GPT-powered чат-бота компании до более высокого уровня качества и персонализации Требования: — Подтвержденный опыт работы с GPT или другими большими языковыми моделями — Практический опыт создания AI-агентов и agentic workflows — Глубокое понимание RAG и опыт его применения в реальных проектах — Уверенное знание Python — Знакомство с векторными базами данных — Опыт работы с LangChain — Понимание LLMOps best practices — Отличный английский для написания промптов и коммуникации с командой — Аналитический склад мышления — Проактивный подход к экспериментам и поиску решений — Интерес к AI и постоянному профессиональному развитию Условия: — Полная занятость — Удалённый формат работы — График 5/2 — Вечерние или ночные смены — Рабочий день 8 часов — Выплаты один раз в месяц — Оформление по договору ГПХ с самозанятым — Заработная плата $2 000–4 500 в месяц до вычета налогов — Работа над AI-продуктом в сфере iGaming — Возможность развивать GPT-powered chatbot и современные conversational AI решения

Location: San Francisco, CA | Seattle, WA | New York City, NY | Washington, DC About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Corporate Security protects the environment Anthropic's people work in every day: their laptops and phones, their identities, the tools they collaborate in and the company data that flows through all of it. Everything that makes Claude what it is sits behind that environment. We keep company access on devices we manage, make those devices hard to compromise and right-size what any one of them can reach, while caring a great deal about the day-to-day experience of the people using them. The company is growing quickly and this team is growing with it, so we treat the work as an engineering discipline: controls as code and automation over queues, built to scale with headcount rather than strain against it. As a Security Engineer here you'll drive significant parts of that work end to end. You'll set technical direction and turn it into shipped tooling. When a control collides with someone's workflow, you'll find the path that keeps them moving without giving up the protection. You'll be handed problems rather than task lists and you'll find as many yourself: threat-modeling the environment to surface what matters, fixing it and bringing the evidence that shapes what the team prioritizes next. This is a senior, hands-on individual contributor role. Key responsibilities Drive endpoint hardening across macOS, Windows, Linux, and ChromeOS, including device management configuration, application allowlisting, patching, and browser policy, favoring controls that are versioned, reviewable, and repeatable over one-off configuration Extend device-trust and zero-trust access controls so company systems are reached from managed devices bound to the right person and carrying the right level of access, treating the experience of fellow employees as a design constraint rather than an afterthought Build the automation and integrations that let the team scale with the company: joiner/mover/leaver automation across identity and device management, exception and expiry workflows, posture-driven policy, and Claude-assisted triage of review queues Lead SaaS and identity governance, including third-party OAuth grants, delegated admin access, chat-platform apps, browser extensions, and software security reviews, turning recurring decisions into policy and tooling Partner across the wider Security team, IT, and Engineering on telemetry, detections, and shared standards, and help define how a company that increasingly runs on AI agents does so securely and at scale Minimum qualifications Hands-on endpoint security engineering on macOS, Windows, Linux, or ChromeOS, such as MDM and declarative device management profile engineering, application allowlisting or binary authorization, system extensions and endpoint security frameworks, or their platform equivalents Proficiency in Python and scripting languages generally; you architect and build integrations, automation, and internal tooling as a normal part of the job, and can write a detection when the work calls for it Working depth in identity and access management, SaaS security, and zero-trust access Threat-modeling judgment that finds the problems worth solving and the ability to scope them, define "done," and drive them to completion Care for Anthropic's mission and the part corporate security plays in it Preferred qualifications Experience defining the scope and choosing the tooling for a security program rather than inheriting it Experience shipping an enforcement change to a large user population: using data to find what will break before it does, staging the rollout, building the alternative path for affected workflows, and moving people onto it ahead of enforcement Endpoint depth across more than one of macOS, Windows, Linux, and ChromeOS, with the judgment to harden for the threats that matter rather than to a checklist Mobile security across managed and BYOD contexts, including protecting people and devices in higher-risk settings such as international travel Experience bringing security governance to a modern SaaS environment, including third-party integrations, delegated access, and the long tail of internally built and AI-generated apps, in a way that speeds decisions up rather than slowing them down Configuration-as-code, infrastructure-as-code, and CI/CD applied to corporate infrastructure LLM-assisted security tooling you built that materially changed what a team could cover, and the judgment to know which work to hand to a model, which to keep, and how to combine the two A track record of getting security controls adopted across an organization through influence and partnership rather than authority Deadline to apply: None. Applications will be received on a rolling basis. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $320,000 — $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Remote - US About the Job: As a Staff Engineer on LaunchDarkly's product engineering team, you'll design and build the next generation platform that helps all LaunchDarkly users (human and agent) interact and use our services. Our product suite enables customers to run A/B tests, measure the impact of feature changes, and optimize experiences, and is integrated with a feature management and observability platform that processes trillions of evaluations daily. This role sits at the forefront of our next generation of user interaction with our suite of products. We have a sophisticated set of users, and we have now learned through working with them and observing their usage patterns what a major redesign can do to help give them a more pleasant, productive, and efficient experience with our products. You'll work across our entire product suite, focusing on understanding the key use cases, building the experiences and the supporting technical platform, and providing guidance and tools for other teams to be able to build better experiences more quickly. Deep technical experience, a scientific mindset, and the ability to influence product and technical direction are critical. You'll lead by example: setting the bar for rigor, mentoring teammates, and owning systems end to end, including on-call. Responsibilities: Build and design our next generation of user experiences (human and agent) across the LaunchDarkly suite. Collaborate with other product teams to ensure they have the tools and platform to build great user experiences. Mentor engineers and raise the team's bar for technical rigor and system design. Own operational excellence for the experience platform - monitoring, observability, incident response, on-call. Robust telemetry and alerting. Qualifications: 10+ years building large-scale products with sophisticated audiences that are looking for help and leverage to do complex work. Has built and designed the interfaces and supporting technology platforms in consumer-grade enterprise applications. Technical leadership: setting direction, writing specs, influencing across teams. BA/BS in mathematics, statistics, data science, or related field, or preferentially a graduate degree. Plus: Go, Python, or similar (we use Go for services, Python for stats). Plus: Event-driven architectures and large-scale data processing for high-volume event ingestion and analysis. Plus: Cloud environments (AWS, GCP) and data stores (ClickHouse, Redis, DynamoDB, Kafka, etc.). Plus: Experiment lifecycle tooling: flag–experiment integration, metric frameworks, automated monitoring. Plus: Familiarity with the competitive landscape (Statsig, Eppo, GrowthBook, Optimizely). Plus: Funnel analysis, causal inference, or Bayesian experimentation experience. Pay: Target pay ranges based on Geographic Zones* for Level 5: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $214,800 - $295,350** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $193,400 - $265,870** Zone 3: All other US locations - $182,600 - $251,020** LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: Remote - US About the Job: LaunchDarkly is seeking a Senior Backend Engineer to join our Experimentation team. The Experimentation team is building one of the company’s most strategic product areas: a platform that helps leading engineering organizations move beyond intuition and make product decisions with real statistical confidence. Sitting at the intersection of large-scale systems, data science, and user experience, the team is creating a best-in-class experimentation product that lets customers set up, manage, and analyze experiments with ease while still earning the trust of even the most rigorous data teams. From warehouse-native analysis to experimentation workflows built on top of LaunchDarkly’s massive feature management scale, this team is tackling ambitious technical problems with visible customer impact and a clear opportunity to define the future of modern software experimentation. As a Senior Backend Engineer, you will design and operate the services that power this product, contribute to technical direction, and help deliver new functionality to customers. You will work closely with product managers, designers, data scientists, and engineers across LaunchDarkly to solve complex, data-intensive problems with meaningful customer impact. Responsibilities: Design, build, and operate scalable backend services and APIs that power LaunchDarkly’s Experimentation product. Own backend components across their lifecycle, including technical discovery, design, implementation, testing, deployment, monitoring, incident response, and continuous improvement. Build and evolve systems supporting experiment setup, event data ingestion, metric computation, results processing, and results presentation. Contribute to architectural decisions and technical proposals, making thoughtful trade-offs around scalability, reliability, performance, cost, and maintainability. Partner with product managers, designers, data scientists, and adjacent engineering teams to translate customer needs and product goals into reliable technical solutions. Collaborate with Data Platform, Warehouse Integrations, SDK, and other teams on shared data flows, services, and cross-team dependencies. Investigate complex production issues, identify root causes, and implement durable fixes. Improve observability, testing, deployment safety, operational processes, and the reliability of the systems you build. Participate in the team’s on-call rotation and take ownership of production systems in a you-build-it-you-run-it culture. Support teammates through thoughtful code reviews, design reviews, knowledge sharing, and informal mentorship. Qualifications: 6+ years of professional software engineering experience, including significant experience building and operating backend services in production. Fluency using AI tools in software engineering workflows, including the judgment to direct, evaluate, and validate AI-generated output. Experience designing and delivering customer-facing systems that are scalable, reliable, observable, and maintainable. Strong programming experience in Go or a comparable backend language such as Python, Rust, or C++. Our team is using Go. Experience with distributed systems, event-driven architectures, data pipelines, APIs, data modeling, or data-intensive services. Familiarity with analytical, operational, or warehouse data stores such as ClickHouse, Postgres, Snowflake, Redshift, BigQuery, Databricks, or equivalent technologies. Experience diagnosing production issues and improving system reliability through metrics, logs, traces, alerting, and other observability practices. Experience working in a cloud environment and with infrastructure-as-code or equivalent deployment and operations tooling. Ability to take an ambiguous problem from discovery and scoping through design, implementation, launch, and ongoing operation. Clear, thoughtful communication and a collaborative approach to working with technical and non-technical partners. Experience with experimentation, A/B testing, analytics, data platforms, or similarly data-intensive products. Pay: Target pay ranges based on Geographic Zones* for Level 4: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $191,800 - $263,670** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $172,600 - $237,270** Zone 3: All other US locations - $163,000 - $224,070** LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @ launchdarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

Location: San Francisco, CA | New York City, NY | Seattle, WA About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic trains and serves Claude across multiple cloud providers and accelerator platforms. The Platform Portability team owns the abstractions, tooling, and deployment infrastructure that make this possible without every engineering and research team needing to become experts in different clouds. As an engineer on Platform Portability, you'll design and build the systems that let us bring up new capacity, ship our platform to cloud provider platforms & marketplaces, and move workloads between providers with confidence. You'll work closely with our cloud partners on capabilities we need that don't exist yet, and with internal Compute, Inference, and Security teams to make "which cloud is this running on?" a question most engineers at Anthropic never have to ask. Your work directly determines how quickly and reliably we can put safe, frontier AI in front of users — wherever they are. What you'll do Our work splits into two workstreams, and we need your help across both. Portable infrastructure. We build the provider-agnostic abstractions for storage, messaging, and connectivity that let Anthropic's systems run on any cloud, and they have to hold up at the scale of frontier model inference. You'll design and build those abstractions, plus the tooling that lets internal teams provision, configure, and operate services across clouds through one consistent interface. You'll also hunt down the provider-specific assumptions hiding in our codebase and set the patterns that keep new ones from creeping in. Claude on partner clouds. We ship Claude onto third-party cloud platforms, and every launch has to be repeatable. You'll own that delivery end to end, including the build, release, and validation pipelines behind it. You'll work directly with engineering teams at our cloud partners and internal infrastructure stakeholders to land the features we need, debug platform issues, and influence their roadmaps. Expect to go deep on native integrations with each provider, and to do the cross-cutting work that keeps our platform consistent across all of them. Across both, you'll shape how the rest of Anthropic builds for multiple clouds. You'll review designs with cloud-portability implications, mentor engineers across the org on multi-cloud patterns, and bring internal stakeholders into alignment through clear writing and conversation. You'll also take your turn in the on-call rotation, and you'll design the postmortems, runbooks, and incident response that help us never fail the same way twice. You might be a good fit if you: Have a minimum of 8 years of practical experience building and operating production distributed systems Own large-scale infrastructure systems and lead ambiguous, cross-team technical projects from design through production Run the same production workload across multiple cloud providers, including the migration or abstraction work that made it possible Understand how cloud IAM models and networking primitives (VPC peering, private connectivity, service mesh) differ across providers Write production code in at least one general-purpose programming language (e.g., Python, Go, or Rust) Work confidently with Kubernetes and Infrastructure as Code (e.g., Terraform, Pulumi) Understand ML infrastructure and supporting interconnects Ship software through hyperscaler marketplaces or managed-model platforms Bring a background in security, compliance, or data residency for regulated or sovereign cloud environments Care about the societal impacts of your work and Anthropic's mission to build safe, beneficial AI Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY, SEA, SF or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Ciudad de México, Mexico Workplace: hybrid Location: Mexico City (Hybrid for Mexico location and remotely for others locations) | Department: Strategy D&A Office Company: NOVACARD Be part of NOVACARD’s transformation into a truly data-driven fintech. We’re looking for a Strategy & Data Governance Analyst — a key contributor bridging business strategy, financial analytics, and enterprise data management. Your mission is to build a data-empowered decision culture: translate data into strategic insights, ensure data quality and governance, and support data-driven business planning. 📝 What You’ll Do – Responsibilities: 📈 Drive Strategic Analytics ·       Analyze company performance across key fintech metrics: acquisition, activation, retention, monetization, and churn. ·       Build and maintain unit-economics models to evaluate channel profitability, LTV/CAC dynamics, and payback periods. ·       Identify growth drivers, operational inefficiencies, and levers for strategic improvement. ·       Provide analytical support for strategic planning, quarterly targets, and investment prioritization. 🧠 Lead Data-Driven Transformation ·       Design and implement a framework for data-driven decision-making across departments. ·       Establish standardized KPI definitions, reporting hierarchies, and accountability chains. ·       Support leadership in translating business goals into measurable data objectives. 🧩 Build Data Governance Framework ·       Coordinate creation and maintenance of core governance artifacts: ·       Metadata descriptions ·       Enterprise Data Catalog ·       Data Lineage (technical and business flow mapping) ·       Business Glossary (data stewards and owners register) ·       Data Quality Rules & Profiling metrics ·       Data Observability & Monitoring dashboards ·       Collaborate with IT, Data Engineering, and Product teams to ensure reliable and transparent data flows. 🔍 Maintain Data Quality & Trust ·       Define and monitor data quality KPIs: completeness, consistency, timeliness, and accuracy. ·       Investigate data anomalies and drive root-cause analysis with responsible teams. ·       Build automated data quality and observability processes within DWH and reporting layers. 🧪 Run Strategic Experiments ·       Design and analyze A/B and multivariate tests supporting product and business hypotheses. ·       Measure incremental impact of product, pricing, and communication changes on key business metrics. ·       Apply statistical rigor to evaluate significance and scalability of experimental results. 📊 Deliver Executive Insights ·       Develop dashboards and reports that translate complex data into actionable recommendations for management. ·       Support financial planning, forecasting, and scenario analysis with data-driven models. ·       Ensure consistent alignment between operational KPIs and strategic company goals. 🤝 Cross-Functional Collaboration ·       Act as an interface between Strategy, Product, Data, and Finance teams. ·       Promote data stewardship culture and educate teams on proper data usage and governance principles. ·       Facilitate adoption of data-governance tools and processes across the organization. 📝 Regular Tasks: ·       Maintain financial and operational KPI dashboards in Power BI (or similar). ·       Conduct deep-dive analyses on acquisition, retention, and monetization metrics. ·       Support management in quarterly OKR reviews with analytical insights and forecasts. ·       Curate metadata, lineage, and glossary entries for critical datasets. ·       Track implementation of governance policies and compliance with data ownership model. ·       Evaluate effectiveness of data quality monitoring tools and workflows. ·       Prepare and present analytical materials for leadership and board-level reviews. 💻 Skills & Tools: ✅ SQL – advanced level for analytics and governance queries. ✅ Python – for modeling, statistical analysis, and data validation. ✅ Power BI (or similar-  Tableau, Looker etc) – for data storytelling and executive reporting. ✅ Data Governance Platforms – experience with Ataccama, Collibra, Alation, OpenMetadata or etc. ✅ DWH & Integration – understanding of pipelines, data lineage, and data catalog integration (Postgres, etc.). ✅ Statistics & Experimentation – hypothesis testing, regression, causal inference, cohort analysis. ✅ Financial & Strategic Analysis – familiarity with unit economics, LTV, CAC, margin modeling. 🌟 Soft Skills: 🗣️ Strategic Communication – ability to distill analytical insights into concise strategic narratives for executives. 🧩 Systems Thinking – connects operational processes, data flows, and financial outcomes. 📋 Project Management – coordinates cross-team governance initiatives. 🔎 Critical Thinking – detects weak points in data logic and decision frameworks. 🤝 Stakeholder Leadership – builds alignment among Product, Risk, Marketing, Operations, Legal, Finance, DWH and IT. 🚀 Change Catalyst – inspires teams to adopt data-driven practices and maintain analytical discipline.

Location: United States, Aliso Viejo, CA Why Sony Interactive Entertainment? Sony Interactive Entertainment isn’t just the Best Place to Play — it’s also the Best Place to Work. Sony Interactive Entertainment (SIE) is the company behind the PlayStation brand. As a subsidiary of Sony Group Corporation, we’re part of a proud legacy of innovation and excellence. SIE is a dynamic technology company, delivering cutting-edge hardware and network services to more than 100 million people and an entertainment leader, home to some of the most beloved and recognizable intellectual properties (IP) in the world. Our role at SIE is to create and nurture the experiences under the PlayStation brand, a name synonymous with entertainment excellence and creativity. Senior Software Engineer – Applied AI & Streaming Aliso Viejo, CA The vision We think AI will change what cloud gaming can be. It can make streamed play faster, more personal, and more accessible, and in some ways better than playing locally. As a Senior Software Engineer on our team, you'll build agents and inference-backed systems into a real-time streaming platform and ship them to players. You'll work where AI meets performance-sensitive systems, and a lot of the problems here are still being defined. What you'll do Design, prototype, and ship AI-powered capabilities across our streaming platform and player experience. Apply inference and agents to real-time performance, player engagement, personalization, and accessibility. Use AI to understand, optimize, and evolve large existing codebases, including our streaming stack. Build and extend our platform in C++, and help shape the technologies and architecture we use next. Build what production AI needs: evaluation, telemetry, guardrails, fallbacks, and attention to latency and cost. Turn ambiguous ideas into demos and experiments, measure what works, and harden it for production. Work AI-natively every day, using coding agents, automation, and rapid exploration, and help the team do the same. Work with a small, focused engineering team and with partners across streaming, platform, and cloud. You're a great fit if you have A BS in Computer Science or a related field, or equivalent practical experience. Senior-level software engineering experience with a track record of owning complex systems end to end. Strong C++ skills from professional work in production codebases. Hands-on experience building and deploying agents or AI-powered features in production. You've worked through evals, regressions, latency, cost, and the ways these systems fail. A strong grasp of how to turn models into products, including context and prompt design, tool use and orchestration, memory and retrieval, model selection, and where inference should run. Fluency with AI-native engineering workflows. Product judgment. You can tell when AI makes an experience better and when it's a gimmick. The ability to work in ambiguity, move quickly, and keep momentum as priorities change. Clear communication, strong ownership, and a habit of making the people around you better. Bonus XP Python, Rust, or other languages used to build and serve AI systems. Low-latency or on-device inference, model optimization, or GPU experience. Real-time media, game streaming, graphics, or video experience. Cloud infrastructure, distributed systems, or production platform experience. Experience building conversational or agentic experiences for games or interactive products. Linux or Windows systems experience. Japanese language or cross-cultural collaboration experience. You enjoy playing video games. Why join us Work on AI problems most engineers never get to. In real-time systems, every millisecond counts, and so does every inference call. Help set the direction. Our AI strategy is still taking shape, and you'll help decide what we build, not just how. Get real ownership. You'll join a small, senior team where ideas go from prototype to production quickly. At SIE, we consider several factors when setting each role’s base pay range, including the competitive benchmarking data for the market and geographic location. Please note that the base pay range may vary in line with our hybrid working policy and individual base pay will be determined based on job-related factors which may include knowledge, skills, experience, and location. In addition, this role is eligible for SIE’s top-tier benefits package that includes medical, dental, vision, matching 401(k), paid time off, wellness program and coveted employee discounts for Sony products. This role also may be eligible for a bonus package. Click here to learn more. The estimated base pay range for this role is listed below. $177,300 — $265,900 USD Please note, Sony Interactive Entertainment conducts background checks at the offer stage for all new employees (which may include criminal background checks for some roles) and will need to process personal information to support these checks. Please refer to our Candidate Privacy Notice for more information about what personal information we collect, how we use it, who we share it with, and your data protection rights. Equal Opportunity Statement: Sony is an Equal Opportunity Employer. All persons will receive consideration for employment without regard to gender (including gender identity, gender expression and gender reassignment), race (including colour, nationality, ethnic or national origin), religion or belief, marital or civil partnership status, disability, age, sexual orientation, pregnancy, maternity or parental status, trade union membership or membership in any other legally protected category. We strive to create an inclusive environment, empower employees and embrace diversity. We encourage everyone to respond. Sony Interactive Entertainment is a Fair Chance employer and qualified applicants with arrest and conviction records will be considered for employment.

Location: San Francisco, CA | New York City, NY About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role The Claude Platform is growing rapidly and serves developers and enterprises at scale. Reaching the next tier of enterprise customers requires transforming how and where we deploy it, as well as the set of features we support out of the box. The Distribution team owns that transformation: making the Claude API a cloud-native, managed product that runs wherever our customers need it, cross-cloud and on Anthropic's own infrastructure, with the enterprise-grade security, compliance, and operational capabilities to support it. This work is split across to major workstreams that are covered in the next section, and we need your help across both. What you'll do Claude Platform on the Clouds: You will make the Claude Platform a best in class offering on the Cloud Service Provider’s platform (AWS, GCP, Azure), by bringing our API, control plane and Anthropic features through the provider’s front door. You’ll do cross-cutting work across the clouds and also have the opportunity to go deeper with CSPs on native integrations across a range of deep technical problems at unprecedented scale. You’ll get to collaborate across the company with teams such as Infrastructure, Systems, Networking, Databases, Inference and more. Enterprise Readiness: You’ll make our platform even more suitable for Enterprise, shipping next gen enterprise enablement features that unblock our next wave of regulated customers or enable our existing ones to scale further. You’ll do so in an Enterprise SaaS context, with a specific focus on enterprise growth, security and compliance, with features ranging from key management & encryption, audit APIs, usage visibility, access control, and international data residency. You’ll also partner closely with core teams across the company, as well as collaborate with CSPs to make these available on our cloud platforms. You might be a good fit if you: Have a minimum of 8 years of practical experience as a backend or platform engineer building scalable distributed systems, ideally operating at tech lead level or equivalent Take a product-focused approach to platform work and care about building solutions that are robust, scalable, and easy to adopt by our customers Own large-scale infrastructure systems and lead ambiguous, cross-team technical projects from design through production and can do so independently. Have experience with cloud infrastructure (GCP, AWS, or Azure) at scale and/or Enterprise SaaS experience in a multi-tenant context, with background in security, compliance or data residency for regulated or sovereign cloud environments. Take full ownership of your work—from design through deployment and operations Are proficient in Python, Go, Rust, or similar systems language Deadline to apply: None. Applications will be reviewed on a rolling basis. Location Preference: Preference will be given to candidates based in NY or the Bay Area given the current location of team. The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: $405,000 — $485,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings. How we're different We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills. The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences. Come work with us! Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.

Location: Espoo Workplace: Hybrid Role highlights: - Senior Fullstack Engineer - Location: Espoo - Department: Engineering, Fleet Control and Communications - Reports to: Engineering Manager, Fleet UI - Employment type: Permanent - Workplace model: Hybrid - Employment is subject to applicable security screening (incl. SUPO, where required) Why this role matters: As a Senior Fullstack Engineer in Fleet UI team you will be building a mission-critical system used by satellite operators. The problems are technically rich: managing satellite configurations, visualizing orbits in 3D, managing passes across a global network of ground stations, automating mission operations and more. You will work in a domain where the UI decisions directly impact satellite mission outcomes. Who We Are ICEYE delivers space-based intelligence, surveillance, and reconnaissance (ISR) capabilities to governments and allied nations. This includes sovereign and turnkey ISR missions leveraging ICEYE’s world-leading synthetic aperture radar (SAR) satellite technology, as well as access to data from the world’s largest SAR satellite constellation. These capabilities enable partners to detect and respond to critical changes anywhere on Earth with unprecedented speed and accuracy – day or night and in any weather, supported by ultra high-resolution imagery and high-frequency revisits. As a trusted partner for defense, intelligence, security, and maritime domain awareness, ICEYE’s near real-time data creates a tactical advantage for mission-critical operations. Designed for dual use, the platform also serves civil protection and commercial users for natural-catastrophe intelligence, insurance, maritime monitoring (including oil-spill detection), and finance, contributing to global security and community resilience. ICEYE is headquartered in Finland and operates globally across Europe, North America, the Middle East, and Asia-Pacific. We have more than 900 employees, united by a shared vision: improving life on Earth by becoming the global source of truth in Earth Observation.   Your day-to-day responsibilities   - Build, and maintain features across a React + TypeScript project serving real-time satellite operations - Collaborate closely with a UI/UX designer in developing sophisticated UI components and data visualizations tools including timeline views, 3D globe rendering (Cesium), and pass planning interfaces - Contribute occasionally to backend APIs (Node, Python) to unblock delivery when needed - Drive frontend architecture decisions — state management strategy, component design, performance optimization - Support the team with DevOps work across multiple environments — including managing Docker-based deployments, configuring environment-specific runtime settings, and contributing to release workflows - Write and maintain unit tests (Jest + Testing Library) and end-to-end tests (Playwright) - Participate in code reviews, uphold coding standards, and mentor engineers on best practices - Contribute to CI/CD pipelines and oversee migration from Webpack 5 to Vite What we’re looking for Must haves: - 5+ years of professional experience building fullstack production-grade applications using React, TypeScript (ES6+) and Node - Experience writing clean, maintainable code in Python - Strong understanding of component-based architecture, modern React patterns, and state management approaches - Experience designing, developing, and consuming RESTful and GraphQL APIs - Solid testing discipline, including unit and end-to-end testing with tools such as Jest and Playwright - Experience with modern frontend tooling and build systems such as Vite, webpack, and npm - Proficiency with Git and collaborative development workflows Active use of AI-assisted development tools - Strong problem-solving skills and ability to debug complex, cross-layer issues - Understanding of web application security best practices - Relevant higher education degree in Computer Science, Software Engineering, or a related technical field Nice to haves - Solid understanding of API design, including REST principles and GraphQL schema design - Knowledge of database design and ORM frameworks - Experience with modern DevOps practices including CI/CD pipelines, containerization, and cloud platforms such as AWS - Familiarity with infrastructure and deployment tooling such as Kubernetes, Terraform, Helm, or ArgoCD Application Process - Talent Partner Screen Call - Hiring Manager Interview - Technical Interview - Values & Fit Interview 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. Base salary range for this position is 6 500 - 9 000 € per month (gross), depending on experience, and will be negotiated individually. 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 http://iceye.com.

Location: Remote (North America) Workplace: Remote ABOUT CLIPBOARD Our mission is to uplift as many communities as possible. We do this through our app-based marketplace that connects healthcare professionals with the workplaces that need amazing workers. This enables hundreds of thousands of people to achieve financial stability for themselves and their families while providing essential care to millions of people across the U.S. Founded in 2016, we are a remote-first team of over 1,000 people building a top Y-Combinator company https://www.ycombinator.com/topcompanies/ and have been profitable since 2022. We’re the leader in Long-Term Care staffing and are rapidly expanding into Home Health, Hospitals, and more, meaning we have more work to do than people to do it, and are growing our team to support millions more people and their communities. ABOUT THE ROLE Clipboard is looking for a Sales Operations Analyst to help build and run the systems behind our sales organization. You'll work across Salesforce, data, automation, and internal tools to help our sales team operate more effectively. That might mean building an automation that eliminates a recurring workflow, investigating a messy data problem, redesigning part of our Salesforce setup, or building a new system from the ground up. We are a small team with an unusual operating model. Much of our execution runs through AI agents that we direct and quality-check, allowing each analyst to operate with the leverage of a much larger team. This is equal parts builder and operator. You'll own systems end to end, work through ambiguous requests from reps and leadership, and be accountable for making sure the things you build actually work. WHAT YOU'LL DO - Own live systems. Take ownership of production systems such as account distribution, deal intelligence, competitor tracking, and data sync pipelines. You'll be accountable for their accuracy and reliability. - Solve ambiguous problems. Work through requests from sales reps, managers, and leadership, figure out what is actually needed, and execute quickly. - Direct AI agents. Write specs and prompts, supervise AI agents, and rigorously QA their output before it touches production data. - Build automations and tools. Create scripts, scheduled jobs, Slack bots, and lightweight web apps that turn recurring manual work into scalable systems. - Analyze and report. Use SQL and other tools to answer important revenue questions and build reporting the organization can trust. - Guard data quality. Handle merges, deduplication, account mapping, enrichment, and other work required to keep our systems accurate at scale. WHAT WE'RE LOOKING FOR - Evidence of building. You've built scripts, automations, tools, systems, or other solutions to real problems. - AI-native working style. You already use AI to multiply your output and understand where it can fail and how to verify its work. - High judgment under ambiguity. You can take a loosely defined problem, figure out what matters, and know when to act versus when to ask. - Strong attention to detail. You're comfortable being the last line of defense before changes affect production systems and large datasets. - Bias to ownership. When something you own breaks, you don't just fix the immediate issue. You look for the underlying problem and improve the system. SQL and Python experience are strong pluses, but we're more interested in your curiosity, judgment, and ability to ship than checking every technical box. NICE TO HAVE - Salesforce administration or development experience, including flows, SOQL, or data model design. - Experience in Sales Operations, Revenue Operations, Business Operations, analytics, or a similar environment. - Experience building automations with tools, scripts, APIs, or AI agents. INTERVIEW PROCESS 1. Application Review – We'll review your experience and evidence of things you've built, automated, or owned. 2. Take-Home Assessment – A practical, ~2-hour assessment using a fictional company, mock website, and CRM. You'll have 48 hours to complete it, and AI tools are encouraged. 3. Technical Walkthrough – A 30-minute session where you'll demo what you built, explain your decisions, and make a small live change to your system. 4. Manager Interview – A 30-minute conversation focused on communication, ownership, judgment, and how you operate under ambiguity. 5. Final Steps / Offer! – Some candidates may have an executive conversation, followed by references and an offer. WHAT WE OFFER - Competitive base salary - Insurance benefits + 401k options - Unlimited PTO and flexible holidays - Remote-first working environment To get a better understanding of the general type of people we want to hire, you can check out our blog here. https://creatingvalue.substack.com/     Quick Note on Scammers: Clipboard would never ask you for money or your bank details to participate in our hiring process. Report any scammers impersonating the Clipboard hiring team members here https://forms.gle/SyGaxHFbon7Hg9fW6.