Вакансии

-Коммерческий опыт работы в роли Frontend-разработчика от 5 лет.

- Design and build the company’s quality engineering platform. - Define testing architecture across unit, integration, contract, API, and end-to-end tests.

Location: Remote, Global Workplace: Remote ABOUT SUPABASE Supabase is the Postgres development platform, built by developers for developers. We provide a complete backend solution including Database, Auth, Storage, Edge Functions, Realtime, and Vector Search. All services are deeply integrated and designed for growth. About the Role We’re looking for a Software Engineer, AI Tooling Infrastructure to join our AI Tooling team and help build and run the backend services behind Supabase’s AI products. The Supabase MCP server is one example of what the team runs in production, alongside the services that support agent skills and the dashboard assistant. You’ll work closely with the Platform, SRE, Auth, Billing and Edge Functions teams, and with the engineers on the AI Tooling team who build the product surfaces. The AI Tooling team runs its own services in production and carries its own on-call. Traffic from AI clients and agents behaves differently from traffic from people: hundreds of calls a minute, retry loops, and no reading of deprecation warnings. This role makes sure the services they use are reliable, correctly authorized and observable. It is a systems and infrastructure role rather than a product AI role, and it is not an SRE role. You will build and operate these systems, not only advise on them. This role is ideal for someone who thrives in async, fast-paced environments, owns what they ship in production, and is excited about building developer tools that scale to millions. WHAT YOU’LL BE RESPONSIBLE FOR In this role, you’ll: - Build and operate the production backend services behind Supabase’s AI products, including the MCP server: deployment, scaling, configuration and release. - Take ownership of how those services are structured, including splitting or reshaping a service when that makes it safer to run and easier to change. - Define, measure and meet reliability targets for the services the team runs. Set SLOs with the SRE team, track error budgets, and use them to decide what to fix first. - Participate in the AI Tooling team on-call rotation, and be a first responder for incidents in those services. Investigate, fix, coordinate with other teams during incidents, and write the follow-ups and runbooks. - Work the AI Tooling team support queue alongside on-call, and turn recurring issues into fixes rather than repeated manual answers. - Own authentication and authorization for AI and agent clients: OAuth apps, scoped tokens, and permissions that make sense for agents as well as humans, including how we change or deprecate a permission without breaking existing integrations. - Own observability for the services the team runs: metrics, traces, logs, dashboards and alerts, so we find problems before customers do. - Handle capacity and abuse for agent traffic: rate limits, cost and safety controls, and behavior under load or when a dependency degrades. - Improve the architecture of the services the team owns as they grow, including splitting or reshaping a service when that makes it safer to run and easier to change. - Work with the Platform team on shared code, review ownership and release process, and with the SRE team on infrastructure, alerting and incident practice. - Contribute to the code of the AI Tooling team’s tools, such as the MCP server, where it affects reliability and security, in partnership with the engineers who own the product surface. YOU MIGHT BE A GOOD FIT IF YOU Must have: - Have 5+ years of experience building and running backend services in production, and have carried on-call for them. - Write strong TypeScript or Go, and are comfortable working in the other. - Have designed and operated APIs with real consumers: versioning, error handling, rate limiting, and backwards-compatible change. - Know OAuth, OIDC, JWT and API authorization well enough to debug them in production and to explain where implementations commonly deviate from the spec. - Have a good understanding of PostgreSQL and relational databases. - Are comfortable with CI/CD, Docker and containerized deployments, and with infrastructure as code. Any tool is fine. - Can debug across services: follow a slow or failing request through several systems using metrics, traces and logs. - Communicate clearly in writing, work with a wide range of stakeholders, and thrive in async, globally distributed teams. - Are comfortable navigating ambiguity and moving quickly. Pick your centre of gravity. We expect you to be deep in at least one of these, and to tell us which: - APIs and auth: You have designed permission models, token scopes or OAuth flows for third-party or machine clients, and you have migrated them without breaking users. - Operations: You have run production services yourself: carried the pager, written alerts and runbooks, used SLOs or similar to decide what to fix, and made shared systems less risky over time. - Gateways and distributed systems: You have built or run proxies or gateways, or debugged hard failures across services (retries, partial failures, upstream outages, fail-open vs fail-closed decisions), and you can reason about load and degradation. Nice to have: - Experience with agent tooling (MCP or similar), or serving traffic from AI agents and LLM clients. - Experience moving a service out of a larger codebase while keeping existing clients working. - Experience with Grafana, OpenTelemetry, Logflare or a similar observability stack, and real SLO work. - Open-source contributions, especially to Node.js, Go, TypeScript or API tooling. WHAT WE OFFER - Fully Remote We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world. - ESOP Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together. - Tech Allowance Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work. - Health Benefits Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us. - Annual Off-Sites Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year. - Flexible Work We operate asynchronously and trust you to manage your own time. You know what needs to be done and when. - Professional Development Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth. ABOUT THE TEAM Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love. - ~400 team members - 60+ countries - 20+ languages spoken - Over $1B raised (including our $500M Series F) - 540,000+ community members We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

As a Developer Experience Engineer at Ritual, you will architect and build the foundational tools that enable developers to efficiently build on our infrastructure. Design and implement best-in-class development frameworks that do for AI-enabled chains what Foundry did for the EVM.

-As a Technical Support Engineer at Turnkey, you’ll help developers integrate, debug, and succeed with our SDKs and APIs across a range of environments — from React and mobile apps to backend servers and CLI tools.

Компания «Top Selection» ищет хорошего специалиста на вакансию « Full-stack разработчик на Go».

Требуемые навыки: #middle, #Анализтребований, #ТестированиеПО, #Автоматизациятестирования, #Ручноетестирование, #Обеспечениекачества, #Playwright, #TypeScript, #CI/CD, #Selenium, #Pytest.

Location: San Francisco Perplexity is seeking energetic researchers and engineers to join our Secure Intelligence Institute (SII), Perplexity's flagship research center for advancing security, privacy, and trust in frontier intelligence. SII’s goals are to advance frontier AI security research, translate those advances into concrete improvements in Perplexity's systems, and share knowledge and resources that strengthen the broader AI ecosystem. As a member of SII, you'll conduct original and impactful research on improving the security and privacy of frontier intelligence systems. Your goal will be to conduct research that is not only rigorous in theory, but practical enough to improve the systems people rely on every day. This work will be informed by the realities of operating general-purpose AI systems used by millions of people and thousands of enterprises, and you'll be expected to translate both your own research and advances from the broader community to practical improvements that protect and defend Perplexity's users. RESPONSIBILITIES - Develop threat models for emerging attack surfaces in AI-native products, including browser, search, and autonomous agents. - Identify and analyze security and privacy threats across AI systems, infrastructure, and user-facing products. - Develop novel defenses, mitigations, and detection mechanisms for security and privacy in AI-native products. - Build security evaluation frameworks, benchmarks, and datasets to measure the effectiveness of different defense mechanisms. - Partner with Perplexity’s Security Engineering team to translate state of the art research into shipped security features and hardened system architectures. - Collaborate with top-tier academic and industry researchers in SII's external research network. - Publish findings at premier venues and contribute to the broader security research community. QUALIFICATIONS - Hold a PhD (or equivalent research experience) in Computer Science, Computer Engineering, or a related field, with a primary focus on security and/or privacy. - Experience publishing at top security conferences (IEEE S&P, USENIX Security, ACM CCS, NDSS) demonstrating original, impactful research contributions. - Deep expertise in one or more of: security of agentic systems, systems security, web and applications security, program analysis, and software security. - Proficiency in Python (bonus points for TypeScript, Go, and/or Rust). - Ability to operate with high independence, willing to dive in and take ownership, and comfortable in a fast-paced environment where research directly informs product. - Clear and concise communcation, translating complex attack narratives into actionable insights for engineering and leadership.

Location: San Francisco, CA, USA About the role Chime Engineering is growing rapidly as we scale to support the financial needs of our members. We are looking for driven engineers to join our Membership team, where you'll work across the full stack, building and evolving the features that deepen member engagement, drive retention, and deliver ongoing value through Chime's membership experience. You will own projects end-to-end, from shaping architecture and designing APIs to building polished front-end experiences and maintaining the ongoing health of the code. In this role, you can expect to Design, develop, test, and scale features across backend services and front-end surfaces that power membership benefits, rewards, and engagement experiences Build and iterate on APIs and UI components that deliver a seamless, high-quality member experience in Chime's mobile app Partner with product, design, data science, and cross-functional stakeholders to understand member needs, define experiments, and ship solutions that move key membership metrics Apply a metrics-driven mindset to decision-making and prioritize efforts based on member and business impact Proactively identify opportunities to improve system reliability, performance, and scalability across the stack Contribute to a culture of technical excellence through mentorship, code reviews, and driving best practices To thrive in this role, you have 5+ years developing software in a production environment at scale Proven experience with Ruby on Rails or comparable frameworks Proficiency with modern front-end technologies (e.g., React, React Native, or TypeScript-based frameworks) A product mindset with a strong bias toward experimentation, iteration, and measuring impact A collaborative spirit and strong communication skills, with experience working cross-functionally Experience working with transactional databases, caching systems, and API design Comfort working across the stack and a desire to understand how all the pieces fit together Experience with experimentation frameworks and data-driven product development is a plus #LI-Onsite #LI-SL1 Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $164,000 — $227,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

Location: San Francisco, CA, USA About the role Jade is Chime’s AI financial partner, helping members better understand and manage their money. We’re looking for a senior software engineer who enjoys building reliable products and systems, solving practical problems, and learning new technologies. You’ll help make Jade more discoverable, relevant, and engaging by connecting members with meaningful AI-powered experiences. You’ll work across the stack, building services, APIs, and member-facing features that power Jade. Our backend primarily uses Python, and we welcome engineers with experience in other languages who are interested in learning it. You’ll also help improve the quality, reliability, and performance of Jade as the product evolves. We value strong engineering fundamentals, thoughtful problem-solving, and curiosity. Prior experience with AI or machine learning is preferred, but not required. In this role, you can expect to Design full-stack services and APIs that support Jade’s capabilities. Own scoped features from technical design through implementation and rollout, with feedback and support from your teammates. Contribute to automated evaluations, testing, and experimentation to understand model behavior, measure quality, and assess the impact of new features. Improve system reliability, performance, and observability, and help investigate production issues. Partner with engineering, product, design, and data teammates to understand member needs and iterate on useful experiences. To thrive in this role, you have 2+ years developing software in a production environment at scale Experience with modern front-end technologies such as React Native, React, or Typescript Proficiency in a backend programming language, such as Python, Go or Ruby, and the ability to write clean, maintainable, and well-tested code. Experience building backend services or applications, including working with APIs and databases. Strong systems thinking, you can reason about how components fit together, how data moves through a system, and where failures might occur. An understanding of distributed systems fundamentals, including service communication, reliability, and trade-offs around latency, consistency, and scale. Strong problem-solving and debugging skills, with the ability to break work into manageable steps and explain technical choices. A collaborative approach, clear communication, and a willingness to ask questions, incorporate feedback, and learn unfamiliar technologies. Experience deploying and supporting a production application, including monitoring, troubleshooting, or working with cloud infrastructure. The following are preferred, but not required: Experience with Python and its backend development ecosystem. Familiarity with large language models (LLMs), including using model APIs, prompts, or tools to build applications. Exposure to AI evaluations (“evals”), such as using test cases, datasets, or experiments to measure response quality and identify regressions. Familiarity with AI tools and frameworks such as LangSmith, LangChain, LangGraph, Amazon Bedrock, or comparable platforms. Experience with any particular tool is not expected. Your exposure to AI can come from professional work, personal projects, or hands-on learning. We welcome strong engineers who are interested in growing into this space. #LI-Onsite #LI-SL1 Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience. Wage Notice $133,000 — $184,000 USD A little about us At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential. We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members. We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress. We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential. Because if we don't—who will? *Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC. What we offer for our full-time, regular employees 🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location. 💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees. ✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life. 🏝 Generous vacation policy and company-wide paid days off 🫂 1% of your time off to support local community organizations of your choice 👟 Annual wellness stipend to use towards eligible wellness related expenses 👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents 👪 Access to family planning reimbursement 💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals. Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact: accommodations@chime.com . To learn more about how Chime collects and uses your personal information during the application process, please see the Chime Applicant Privacy Notice .

Location: Hybrid About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. About the Role Cloudflare’s API Experience team builds the tools and standards that make our API dependable and easy to use. We maintain SDKs and our Terraform provider, build code generation tooling, and are developing API versioning. We’re looking for a senior engineer who cares about the details developers live with: clear interfaces, predictable behavior, useful errors, and upgrades that don’t break their code. You’ll work across languages and teams, help internal engineers ship better APIs, and respond directly to customers. Their feedback will help shape what you build. Responsibilities Build and maintain our SDKs, Terraform provider, and the code generation tooling behind them. Develop API versioning and compatibility practices that let our API evolve without leaving customers behind. Improve API governance: consistent schemas, clear standards, and checks that catch problems before release. Support internal teams daily and work directly with customers to investigate issues and turn recurring friction into lasting improvements. Own projects from design through release and ongoing maintenance. Desirable Skills, Knowledge, and Experience 5+ years of experience building large-scale software applications. Deep Go expertise, with experience building and maintaining production software. Fluency across languages such as TypeScript and Python, and an understanding of what makes a library feel natural in each. Experience building, maintaining, or contributing to a Terraform provider. Experience shipping SDKs or client libraries, including testing, releases, dependency management, and backward compatibility. Well-reasoned opinions about API design and developer tooling, paired with the ability to listen, explain tradeoffs, and make practical decisions. Strong technical judgment built through experience: you can untangle complex problems, set a clear direction, and lead projects from early design through delivery. A track record of helping junior engineers grow through thoughtful feedback, mentoring, and opportunities to take ownership. Experience using AI and automation to improve engineering workflows, with the judgment to identify where they add value and verify the quality of their output. Bonus Points Experience versioning an API, building schema-driven code generators, or establishing API governance is especially valuable. We’re interested in what you’ve built, how you’ve maintained it, and what you’ve learned from the people using it. Experience managing containerized workloads at scale using Kubernetes, Docker, or similar orchestration platforms. Familiarity with CI/CD pipelines and automated testing strategies for infrastructure. Contributions to open-source systems software projects or active participation in the broader systems engineering community. What Makes Cloudflare Special? We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul. Fundamental to our mission to help build a better Internet is protecting the free and open Internet. Project Galileo : Since 2014, we've equipped more than 2,400 journalism and civil society organizations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost. Athenian Project : In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration. Since the project, we've provided services to more than 425 local government election websites in 33 states. 1.1.1.1 : We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released. Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that no user data is sold to advertisers or used to target consumers. Sound like something you’d like to be a part of? We’d love to hear from you! Please note that applicants who progress to the offer stage of the interview process may be asked to attend an in-person interview within one of the Cloudflare Offices or Cloudflare Hubs.  More details about this will be available at that stage of the interview process. This position may require access to information protected under U.S. export control laws, including the U.S. Export Administration Regulations. Please note that any offer of employment may be conditioned on your authorization to receive software or technology controlled under these U.S. export laws without sponsorship for an export license. Cloudflare is proud to be an equal opportunity employer.  We are committed to providing equal employment opportunity for all people and place great value in both diversity and inclusiveness.  All qualified applicants will be considered for employment without regard to their, or any other person's, perceived or actual race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. We are an AA/Veterans/Disabled Employer. Cloudflare provides reasonable accommodations to qualified individuals with disabilities.  Please tell us if you require a reasonable accommodation to apply for a job. Examples of reasonable accommodations include, but are not limited to, changing the application process, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment.  If you require a reasonable accommodation to apply for a job, please contact us via e-mail at hr@cloudflare.com or via mail at 101 Townsend St. San Francisco, CA 94107.

Location: EMEA - Remote Workplace: Remote ABOUT POLYGON LABS Polygon Labs is a global blockchain payments company building and operating infrastructure to move money instantly, reliably, and at internet scale, with the mission to move all money onchain. It is building the Polygon Open Money Stack, an open and integrated stack of services and technologies to instantly and reliably move money anywhere, and put it to work. Its infrastructure has facilitated trillions of dollars in onchain value transfer and supported millions of transactions daily for some of the globe's largest banks, fintechs, enterprises, and consumer applications. YOUR ROLE You will independently execute defined infrastructure work that keeps Polygon's production systems reliable, secure, and operationally efficient. This role is hands-on and operational, with a focus on cloud infrastructure, Kubernetes, infrastructure as code, observability, incident response, and the secure lifecycle of secrets and configuration across services. You will work core hours overlapping with the EU business day and contribute as a trusted infrastructure partner, including reviewing and approving infrastructure changes and supporting production systems through incidents and continuous improvement. YOUR RESPONSIBILITIES - Operate production Kubernetes environments on GKE, including day-to-day cluster operations, troubleshooting, maintenance, and reliability improvements. - Build and maintain infrastructure as code using Pulumi, including Pulumi ESC for environments, secrets, and configuration, primarily in TypeScript and Python. - Manage GitOps workflows with ArgoCD and maintain reliable CI/CD pipelines, including diagnosing pipeline-level race conditions. - Operate GCP infrastructure across IAM, Pub/Sub, Cloud SQL, VPC, and Secret Manager. Tune Pub/Sub subscriptions through settings such as acknowledgement deadlines, dead-letter queue redrive behavior, and backlog alerting. - Manage Cloudflare entirely as code, including Workers and DNS, and maintain lifecycle cleanup for stale preview environments. - Own the secrets and configuration lifecycle across services, including provisioning, rotation, naming conventions, and preventing cross-service authentication drift. - Respond independently to production incidents through triage, escalation, documentation, runbooks, and incident.io http://incident.io workflows. - Review and approve infrastructure pull requests, helping maintain a high standard for safety, correctness, and operational readiness. - Build and maintain Grafana dashboards and alerts, with working knowledge of the underlying agent and collector layer, including Grafana Alloy. - Execute SOC2-driven infrastructure and security work and maintain appropriate separation between regulated or sensitive-data environments. - Read and contribute to systems involving Go, TypeScript, and Python. WHAT YOU'LL NEED - Demonstrated production experience operating Kubernetes on GKE in a day-to-day infrastructure or platform engineering capacity. - Hands-on Pulumi experience, including Pulumi ESC for managing environments, secrets, and configuration, with practical proficiency in both TypeScript and Python. - Experience with ArgoCD, GitOps workflows, CI/CD pipelines, and debugging pipeline-level race conditions. - Strong hands-on experience with GCP services including IAM, Pub/Sub, Cloud SQL, VPC, and Secret Manager, including subscription-level Pub/Sub tuning and alerting. - Experience managing Cloudflare Workers and DNS as code, including cleaning up stale preview environments. - Experience owning secrets and configuration across services, including provisioning, rotation, naming conventions, and preventing cross-service authentication drift. - Demonstrated ability to independently triage and manage production incidents, including escalation, runbooks, and incident.io http://incident.io workflows. - Ability to execute infrastructure work independently from defined requirements without requiring architecture-level hand-holding. - Experience reviewing and approving infrastructure changes through pull requests. - Working knowledge of Grafana dashboards, alerting, and the Grafana Alloy or comparable agent and collector layer. - Security and compliance literacy, including the ability to execute SOC2-driven infrastructure work and operate effectively in regulated or sensitive-data environments. - Ability to read Go and work comfortably across TypeScript and Python codebases. - Availability to work core hours overlapping with the EU business day. POLYGON LABS PERKS The goal of the Polygon Labs total rewards program is to support the health and well-being of you and your family. Our comprehensive compensation plan includes the following benefits for our full time employees: - Remote first global workforce - Industry leading Medical, Dental and Vision health insurance* - Company matching 401k with 3% match* - $1,500 Home Office Set Up Allowance (life-time max) - $200 Annual Book Allowance Program - $75 Monthly internet or phone reimbursement - Flexible Time Off - Company issued laptop - Egg freezing, mental health, and employee wellness benefits *In certain countries medical, dental and vision is fully covered for employees & their dependents. This is country and plan specific. *401k is for United States employees only Polygon Labs is committed to a diverse and inclusive workplace and is an equal opportunity employer. We do not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. Polygon Labs is committed to treating all people in a way that allows them to maintain their dignity and independence. We believe in integration and equal opportunity. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. If you think you have what it takes, but don't necessarily meet every single point on the job description, please still get in touch. We'd love to have a chat and see if you could be a great fit. Learn More about Polygon Labs Website https://polygon.technology/ |Twitter https://twitter.com/0xPolygon|Telegram https://t.me/polygonofficial |Reddit https://www.reddit.com/r/0xpolygon/ |Discord https://discord.gg/0xpolygoncommunity |Instagram https://www.instagram.com/0xpolygon/ |Facebook https://www.facebook.com/0xPolygon.Technology |LinkedIn https://www.linkedin.com/company/13449964/admin/

Location: United States Senior Engineering Manager, Data & AI Lead the engineering team behind Foundry, Insights, Intel, and Voice: the agents, analytics, and data intelligence of the modern freight platform. About the Role Remote, United States. Some travel is required for team onsites, customer visits, and industry events. Relocation assistance is not provided. The Senior Engineering Manager, Data & AI leads the engineering group behind Foundry, Insights, Intel, and Voice. You'll own the group's technical strategy, delivery, and quality, hire and develop its engineers, and stay hands-on by prototyping, writing evals, reading traces, and reviewing architecture in depth. The team is about eight engineers today and growing. It also owns the shared foundation those products run on: a context graph that connects loads, trips, carriers, drivers, customers, documents, and conversations; event-sourced platform data streaming into the warehouse; and the evals, tracing, guardrails, and model routing every agent depends on. Alvys facilitates more than $1 billion in funds every month across invoices, carrier payments, and driver settlements. Behind that volume is one of the richest operational datasets in freight. This team turns it into agents that do real work and intelligence customers can't get anywhere else. Engineering leaders at Alvys are builders. Expect to spend about a third of your time building. You'll set the standard for how an AI-first team works: coding agents in the daily workflow, evals before scale, and production evidence over demos. The platform runs on .NET (C#, and increasingly F#), TypeScript, and Python on Azure and AKS, with Cosmos DB, Postgres, Elasticsearch, Snowflake, dbt, and Fivetran underneath. We're looking for someone who treats AI as a first-class material, both in what we build for customers and in how the engineering team works. Industry Insight Freight runs on phone calls, emails, PDFs, and tribal knowledge. The U.S. trucking industry is worth approximately $1 trillion today and is projected to grow by roughly 60% to nearly $1.5 trillion over the next decade. Yet the work that moves that freight is still largely manual. Nearly 580,000 active U.S. motor carriers operate in a highly fragmented market; 91.5% run 10 or fewer trucks, and 99.3% run 100 or fewer. Few of these businesses will ever build a data team of their own. Every check call answered, rate confirmation read, and exception caught by software is time back for a small team running on thin margins. Freight data is also structurally messy. A single load spans brokers, carriers, drivers, shippers, and documents, each with its own identifiers, and the truth lives across EDI messages, phone calls, and free text. Generic AI tooling doesn't model any of this. That's why we're building a context graph grounded in how freight actually moves. Agents can now answer the phone, read documents, query operational data, and take actions inside a TMS. In freight, those actions move trucks and money. They must be correct, auditable, and safe. About Alvys Alvys is building the operating system for modern freight. Our AI-powered, cloud-native platform brings dispatch, driver mobile, safety and compliance, billing and settlements, native EDI, reporting, integrations, and automation into one product. We were founded in 2020 by freight industry insiders who were tired of software built by people who had never moved a load. That combination of deep customer empathy and ambitious technology still defines us. We visit customers, learn how the work actually happens, prototype quickly, debate ideas openly, and turn the best ones into products people rely on. More than 3,000 trucking and brokerage companies use Alvys today, including larger fleets with increasingly sophisticated operations. We've raised $77M to date, including a $40M Series B. That gives us real momentum and room to make bold bets, while remaining early enough that a great engineering leader can materially shape the product, team, and company. We are building more than a modern interface for a traditional TMS. Foundry, our agent platform within Alvys, helps freight teams make decisions and complete work, and this team builds it. You'll work with curious, direct, low-ego people who solve hard problems, move quickly from prototype to production, and measure customer impact. Our Principles AI makes building cheap. It does not make judgment cheap. The constraint has moved from writing code to deciding what to build and proving it is right. Agents belong in the middle of the pipeline. People remain accountable at both ends. These principles turn that into how we work every day. Own the outcome You own what you ship. "AI wrote it" is not an answer. Judgment stays human. People decide what matters and whether the result is correct. Verify independently Generation and verification are separate. Tests, review, and approval run independently of the agent that did the work. Autonomy is earned per workflow. Agents advance only on measured precision against human-verified outcomes. No number, no promotion. Design for control AI-first means security-first. Customer data stays on approved infrastructure under managed identity. Cost is an engineering constraint. Every shared workflow has termination conditions and bounded fan-out. Build durable systems Knowledge is tool-agnostic. Reviewed intent lives once; vendor-specific machinery is generated from it. Multiple vendors are a design assumption. Durable workflows don't couple to one model or harness. Twice is a pattern. Automate repeated work and share it within 48 hours. The Data & AI Portfolio The Data & AI portfolio covers Foundry, our embedded automation and agent platform, including a unified agent chat that answers questions and takes actions; Insights, conversational analytics grounded in each customer's own operating data; Intel, proprietary data intelligence drawn from third-party, licensed, and proprietary data sources; and Voice, AI voice and chat agents for load status, driver check calls, and the follow-ups in between. It also includes the shared foundation: the context graph, the data platform that feeds it, and the evals, tracing, guardrails, and model routing behind every agent. Why This Role Few engineering leadership roles combine frontier AI work, a proprietary dataset, and an industry this underserved. This one does. You build at the frontier, in production. Context graphs, self-learning agents, voice agents, and agentic automation are still being figured out across the industry. Here you ship them to real customers, on live freight operations, not benchmarks. You work with data no one else has. More than 3,000 trucking and brokerage companies run on Alvys, and more than $1 billion in funds moves through the platform every month. Combined with third-party and licensed sources, that data is the raw material for intelligence no single fleet or brokerage could build alone. Your work changes how an industry operates. With 91.5% of carriers running 10 or fewer trucks, most of our customers will never hire a data team. The agents you build give a small business the leverage of a much larger one. You own a portfolio, not a feature. Four products share one platform. You set its architecture, choose its models and vendors, and decide where the team invests as it grows. You shape the team from the start. The group is about eight engineers today. You'll hire the next wave and set the standard for how an AI-first engineering team works at Alvys. You stay close to the decisions. You report to the Head of Engineering, work directly with customers and our Forward Deployed Engineering team, and have a direct line into company planning, backed by a $40M Series B. What You'll Be Responsible For Leading and Growing the Team Manage, coach, and develop a team of about eight engineers, including senior engineers and tech leads, and grow it as the portfolio expands. Hire senior and staff engineers, and keep the quality bar high as the team scales. Run the team AI-first, with coding agents in the daily workflow and clear standards for how AI-written code is reviewed, tested, and shipped. Owning Technical Strategy Set technical direction for agents, data, and the context graph, and make the build, buy, and model calls with cost, quality, and speed in view. Make tradeoffs across four products that share one platform, including what gets built, what gets cut, and where the team invests. Building Agents That Learn Own the agent development lifecycle from prototype to production to continuous improvement. Build self-learning loops so agents improve from outcomes, user corrections, and transcripts, and make that improvement measurable. Make evals a release gate. No agent ships without tests for quality, safety, latency, and cost. Data and the Context Graph Own the context graph that links loads, trips, carriers, drivers, customers, documents, and conversations, and the entity resolution that keeps it trustworthy. Partner on the data platform that feeds it, including event streams, CDC into Snowflake, data quality, and lineage, so agents and analytics share one source of truth. Capture decision traces (the inputs gathered, the rule applied, any exception, who approved it, and why) so precedent becomes searchable for agents and people, while rules stay explicit. Combine third-party, licensed, and proprietary data sources into intelligence customers can act on, with the provenance, licensing terms, and tenant boundaries of each source respected. Safety, Isolation, and Reliability Design agents that change data with scoped permissions, human approvals, and audit trails, and defend against prompt injection and tool misuse. Enforce tenant isolation and least privilege across every agent, tool, and data path. Own reliability and unit economics. Track cost per task, per call, and per tenant, and keep margins healthy as usage grows. Staying Hands-On Spend about a third of your time building: prototype, write evals, read traces, and debug production. Review your team's designs and code with real depth, and stay current on models and tools, separating what works in production from what demos well. Cross-Functional Partnership Work as a peer to product and design leadership on direction, architecture, sequencing, and delivery. Work directly with customers and our Forward Deployed Engineering team, and turn repeated patterns into platform features. The AI Fluency We Expect We measure AI fluency by how you verify, not by how much you use AI. More autonomy is not always better. You match the level of autonomy to the risk of the work, and you hold yourself and the team to the same five competencies. Delegation: You decide whether to use AI at all, which task to hand off, and how much autonomy it gets. Description: You state goals, requirements, and limits clearly, from a single prompt up to project instructions, specs, and policy. Discernment: You check output against evidence: diffs, acceptance checks, evals, and production monitoring. Diligence: You own the effects, including data access, permissions, memory isolation, budgets, and kill switches. Systems: You know how models, context, tools, harnesses, and memory work, and where each one fails. How You Work With Agents Design multi-agent systems on paper before you build them. For each step, choose a rule, a small model, a frontier model, or a person, and measure cost per outcome, not cost per token. Start from code-orchestrated workflows and add model-led autonomy only where the task needs exploration. Keep agent-to-agent handoffs few, and give each agent a contract: inputs, allowed tools, and output schema. Put limits in code, not in prompts: hooks, sandboxed worktrees, and a stop condition, retry cap, and budget on every loop. Separate the agent that writes from the agent that checks, and give the checker fresh context. Work in an explore, plan, execute, verify, and compound rhythm, where every correction becomes a rule, skill, hook, or test. Move fluently across Claude Code, Codex, and Cursor, and choose an editor-first or agent-first surface based on who should hold the controls for the next step. Where You Take the Team Bring every engineer to running goal-based loops, where specs and checks are written first, never weakened to pass, and run by the agent itself. Move the team from steering every turn to designing the system that steers the agent: its context, its harness, and its loop. Build toward agents that run continuously in hosted sandboxes, each with its own least-privilege identity, a named owner, a budget, and a tested kill switch, with risk-scaled human review on financial actions, auth, settlements, and customer data. Close the improvement loop. Capture traces, run error analysis on real failures every week, encode the fixes, and gate every change to rules, memory, or evals behind evals and a human approver. Self-improving never means self-approving. Minimum Qualifications 8+ years building software, including 3+ years managing engineers. You've grown senior engineers and tech leads and remain a hands-on builder who can prototype, debug production, and review code credibly. Production LLM systems. You've shipped LLM-powered products to real users, not demos, and can explain what broke, what you measured, and what you changed. Agentic engineering in your own work. You build with coding agents every day and can show the multi-agent workflows, contracts, hooks, and loops you put into production, and the checks that kept them honest. Depth in agent systems. You've built with tool use, function calling, MCP, orchestration, memory, and retrieval, and you understand where agents fail. Evaluation discipline. You've built eval systems that combine offline suites, online metrics, human review, and transcript analysis, and used them to gate releases. Strong data engineering judgment. You've worked with event streams, CDC, cloud warehouses, dbt, and data quality, and you know how the shape of the data limits what models can do. Distributed systems in production. You've designed and operated production services with real reliability requirements. Multi-tenant security. You've secured multi-tenant SaaS and isolated customer data, and you treat agent permissions as a security boundary. Language fluency. You write Python or TypeScript fluently and are comfortable reading C#, F#, and .NET. Experience with F# or another functional language is a plus. Startup-stage fit. You've operated at Series B/C velocity amid ambiguity, thin support, competing priorities, and a bias toward shipping and learning. Clear technical communication. You can explain a tradeoff to an engineer, a customer, and an executive. Preferred Qualifications Knowledge graphs, context graphs, entity resolution, or GraphRAG in production. Real-time voice agents, including telephony, speech-to-text, text-to-speech, turn-taking, and latency budgets. Fine-tuning, reinforcement learning from feedback, or prompt optimization against eval sets. Embedded automation or workflow platforms such as Activepieces, n8n, or Temporal. SRE experience, or a record of running systems other teams depend on. Logistics or freight experience, or another vertical where data is deeply entangled with operations. Founder or early-stage engineering leadership experience. A history of hiring, growing, and retaining excellent engineers. Built by people who've moved freight. Come build the intelligence layer with us. Learn more at alvys.com

— Разработка и поддержка сквозного функционала: от высокопроизводительных сервисов на Java до клиентских интерфейсов на React. — Проектирование и оптимизация серверной логики на Java Core / Spring Boot для обработки on-chain данных и ZK-доказательств.

— Проектирование сложных реактивных интерфейсов для мониторинга ZK-пруверов и кросс-чейн транзакций. — Оптимизация производительности приложений и работа с состоянием (Pinia / Vuex).

Location: San Francisco, CA; Bellevue, Wa Workplace: Hybrid About Niantic Spatial We are building for the >80% of economic activity that happens beyond the reach of screens. AI has learned from the text, images and video online, but it still lacks an accurate understanding of physical space. That’s one of the biggest unsolved problems in AI, and it’s the one we’re solving at Niantic Spatial. We build spatial AI models and services so people and machines can reason, learn and act safely in the physical world. We turn camera imagery, video, sensor data and archives into accurate, AI-readable representations of real places that robots can train in and machines can use to know exactly where they are. In physical AI, mistakes have real consequences. That’s why we build AI grounded in measured reality, not guesswork, so the people and machines relying on it can trust it to get things right. Our team built some of the world’s most widely used maps. Now we’re building something bigger: a living, measured record of the real world that machines can query, learn from and use to understand how places change over time. If you want to help AI understand the world we actually live in, come build with us. About the Role You’ll join a small infrastructure team with broad, shared ownership — the engineers who keep Niantic Spatial running. The team covers the cloud platform, the developer tooling every engineer depends on, and the edge services our customers’ requests pass through. You’ll work across SRE, infrastructure, and developer platform alongside teammates who know the stack well, and you’ll grow into owning parts of it yourself. Because every engineer here builds on what this team provides, your work will also shape how the whole engineering org builds, ships, and operates. What You'll Do - Cloud and SRE: Build and maintain cloud infrastructure as code, and help improve reliability through monitoring, alerting, and service-level objectives. - Developer Platform: Help run our source control, CI/CD pipelines, and build infrastructure so engineers can ship quickly and safely. - Production Operations: Share on-call, take part in incident response and follow-up, and automate away repetitive operational work. - Edge and Delivery: Help run the edge API gateway, CDN, and authentication and authorization systems with the rest of the team. - Compute and GPU Management: Help provision and monitor compute and GPU capacity across teams. - AI-Assisted Operations: Use AI tools to help build, automate, and maintain our infrastructure, and help shape how the team uses them. What You'll Bring - Years of Experience: 3+ years in infrastructure, SRE, DevOps, or platform engineering. - Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Infrastructure as Code: Experience managing infrastructure as code with tools such as Terraform, Pulumi, or similar. - Cloud: Hands-on experience with GCP, AWS, or another major cloud provider in production. - CI/CD: Experience building and maintaining CI/CD pipelines in GitLab, GitHub Actions, or similar. - Containers: Production experience with containers and container orchestration, such as Kubernetes. - Core Technical Skills: Proficiency in at least one programming language such as Python, Go, TypeScript, or C++, plus shell scripting and Linux systems. - AI in Your Workflow: Comfort using AI-assisted tools in your engineering work, or a strong interest in building that habit. We’ll help you ramp up on how we use AI here. Nice to Have - Familiarity with API gateways, load balancers, or CDNs. - Familiarity with modern authentication and authorization, such as OAuth 2.0, OIDC, or cloud IAM. - Experience with GPU workloads or ML infrastructure. - Experience with message queuing systems. Location & Work Model This role is based in our San Francisco or Sunnyvale, CA office, or in Bellevue, WA. We work in a high-collaboration environment and ask team members to be on-site a minimum of 3 days per week. Compensation & Benefits The base salary range for this position is $171,000 - $230,000 for Bay Area candidates and $162,500 - $218,500 for Seattle/Bellevue candidates. Actual salary is based on assessed skills, experience, and location. This role is also eligible for equity, bonus, and benefits. Your recruiter can answer questions about total compensation during the hiring process. Inclusive Application We know the strongest candidates don't always tick every box. If you're excited about this role and believe you could do it well, we encourage you to apply even if your experience doesn't match every qualification listed — you may be exactly who we're looking for. Equal Opportunity Niantic Spatial is an equal opportunity employer. Individuals seeking employment at Niantic Spatial are considered without regard to race, color, ancestry, national origin, religion, creed, age, gender (including pregnancy, childbirth, breastfeeding or related medical conditions), marital status, physical or mental disability, medical condition, genetic information, military or veteran status, gender identity, gender expression, sexual orientation, or any other protected category under applicable laws. Niantic Spatial will also consider qualified applicants with criminal histories in accordance with applicable laws. Please contact your recruiter if you want to request an accommodation for the job application or interview process. Candidate Privacy I understand that by submitting my job application, the information I provide as part of that application will be used in accordance with Niantic Spatial's Privacy Notice for Job Applicants and Candidates https://www.nianticspatial.com/applicant-privacy-notice.

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: North Macedonia; Bosnia and Herzegovina; Czechia; Croatia; Moldova; Bulgaria; Montenegro 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