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Location: San Francisco, CA; New York, NY Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO As an Agent Strategist https://sierra.ai/blog/agent-strategist-your-phd-in-applied-ai on a Flagship Deployment, you’ll lead the end-to-end deployment for one of Sierra’s largest and most strategic customers. You own how Sierra's AI agents come to life, often managing scaled deployments as well as new proofs of concept within the same account. You sit at the intersection of product, building agents and customer-facing work, and stay just as close to the technology as you are to the people you build for. You transform a customer's thorniest, highest-stakes problems into agents that measurably move their business. - Own the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle. Take agents from initial scope through conversation design, tooling, and evaluation, to launch and continuous iteration in production — translating business goals into an agent that outperforms, and tuning relentlessly until it's the best version of itself in the real world. You'll have real ownership and autonomy over the outcome. - Be the trusted strategic advisor to enterprise leaders. Sit shoulder-to-shoulder with our customers' executives, understand what success actually means to their business, and shape the AI strategy that gets them there. - Partner with the customer's working teams and executives day to day. Oversee overall program management while ensuring ongoing executive alignment on the long term roadmap. - Navigate enterprise complexity with cross-functional teams (engineering and product). At this scale, every big technical discussion is also a negotiation — you'll need to read the implications in real time, hold your ground, and steer toward the right outcome. Expect to work across business units, procurement, compliance, and senior execs. - Directly impact product. Surface unmet needs from your customer work, and feed them back to research and platform to shape where Sierra goes next. - Manage internal resourcing requirements. Ensure that your deployment is appropriately resourced today and into the future - Drive financial success for both the customer and Sierra. Ensure value exchange is optimized, drive revenue upside for Sierra, and work internally to manage down cost to serve over time, improving margins. - Partner with Sales on commercial strategy. You are a key player in closing new business within the deployment by identifying opportunities, aligning resources, and EXAMPLE PROJECTS These are the kinds of projects that strategists on our team have worked on recently: - Plan, organize, and execute on-site business reviews onsite at a Fortune 100 company with Sierra cofounders in attendance - Manage a portfolio of agents across a customer deployment as they scale nationally, to new use cases, and grow in technical complexity - Build relationships throughout the customer’s organization, unlocking high trust, social capital, and ultimately new ARR - Stand up an agent for a commerce customer that troubleshoots a broken device end-to-end and personalizes product recommendations in the same conversation. - Partner with product on a net-new capability — a new agent architecture or self-service tooling — using a live customer as the design partner. - Define the evaluation and quality bar for a new agent, then use those metrics to drive a measurable lift in outcome https://sierra.ai/blog/outcome-based-pricing-for-ai-agents week over week. WHAT YOU’LL BRING - Proven track record: 10+ years of relevant experience driving results in high stakes situations in an enterprise customer facing role, ideally in a dedicated, embedded model with a named enterprise account — you know what it means to be accountable for a relationship at that depth. - Customer obsession. Genuine energy being in front of customers — understanding their business and needs, thriving in complex organizations, and building trusted relationships. - Communication. Clear, direct, and persuasive across technical and non-technical audiences. - Strategic problem-solving in ambiguity. Strong analytical and critical-thinking skills to break down complex problems, spot risks early, and adapt as things change fast. - Technical aptitude. Comfortable engaging directly with technical concepts - reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in a design discussion. - Ownership and delivery. A track record of running multiple complex, high-visibility projects at once and driving them to outcomes. EVEN BETTER... - You've run a company, business unit, forward deployed team, or have comparable experience in general management of business initiatives that require technical aptitude, strategic leadership, operational excellence, and financial outcome accountability. - Experience building or deploying AI/LLM agents in production — hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) — working closely with technical counterparts. - A degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience — and/or an MBA or comparable experience at the intersection of technology and business. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Location: United States; Canada (BC & ON only) Workplace: Remote Webflow is the agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences that drive predictable growth and strengthen brand trust. Building at Webflow will need grit, because we move fast, without ever sacrificing craft or quality. We're looking for a Staff Product Designer to lead design across the Content and Localization teams on our Build pillar. You’ll help shape Source by Webflow https://webflow.com/blog/introducing-source-by-webflow, our new platform where marketing teams and agents build and optimize digital experiences together. Source is where the hard work of web marketing happens: scaling what works, driving impact with every iteration, and keeping brand and content consistent as teams and agents move at speed. You'll own the Agentic CMS experience: a next-generation content layer that enables enterprise teams to manage content and deliver it across every site, channel, and AI agent they operate. This work spans the full content lifecycle, from authoring and governance to localization and publishing. This is a role for someone who thinks in systems, sweats the details, and gets excited about making complex content infrastructure feel simple — so marketers can move fast, agents can operate reliably, and every experience a brand ships stays coherent and on point. ABOUT THE ROLE: - Location: Remote-first (United States; BC & ON, Canada) - Full-time - Permanent  - Exempt - The cash compensation for this role is tailored to align with the cost of labor in different geographic markets. We've structured the base pay ranges for this role into zones for our geographic markets, and the specific base pay within the range will be determined by the candidate’s geographic location, job-related experience, knowledge, qualifications, and skills. - United States  (all figures cited below are in USD and pertain to workers in the United States) - Zone A: $191,700 - $230,000 - Zone B: $180,000 - $216,000 - Zone C: $168,300 - $202,000 - Canada (figures cited below are in CAD and pertain to workers in ON & BC, Canada) - 209,000 - 251,000 This role is also eligible to participate in Webflow's company-wide bonus program. Target amounts are a percentage of base salary and vary by career level. Payouts are based on company performance against established financial and operational goals.  Please visit our Careers page https://webflow.com/careers#pay-zones for more information on which locations are included in each of our geographic pay zones. However, please confirm the zone for your specific location with your recruiter. - Application Information: - Application deadline: applications accepted on an ongoing basis until position is closed and filled - This posting is for an existing vacancy - Reporting to the Senior Director of Product Design As a Staff Product Designer you’ll …  - Own the Agentic CMS experience end-to-end, from early discovery and UX strategy through prototyping, detailed execution, and making sure what we ship is great. Define how enterprise marketing teams author, organize, govern, and publish content across multiple sites and channels — and how that experience holds together as a coherent system, from the visual authoring surface to publishing workflows to localization. - Design for both humans and agents. Build surfaces that work for marketing teams operating at scale and for AI agents querying and composing against structured content, with the right controls, transparency, and trust signals for each. - Think in systems. The CMS touches nearly everything Webflow's enterprise customers do. Hold a coherent experience model across interconnected surfaces while making individual flows feel simple and obvious. - Work upstream. Partner with PMs, engineers, and researchers to shape what gets built. Align on content models, API affordances, and product strategy before pixels get pushed. - Raise the bar — in craft, process, and how you use AI to move faster without sacrificing quality. Present work to cross-functional partners and senior leaders, and bring a point of view on how the CMS connects to the broader Webflow platform. ABOUT YOU: Requirements: - BA/BS degree or equivalent experience - 7+ years of product design experience with a portfolio showing recent, substantive work navigating ambiguous problems within complex products. You know how to make something complex feel obvious to the people using it. Experience with content systems, multi-user workflows, and agentic experiences is especially relevant.  - Systems thinking at scale. You've designed for interconnected surfaces where decisions in one place ripple across others, and  - Comfort with technical depth. You can engage meaningfully with engineers on API design, data modeling, and content architecture to ensure design and systems decisions are aligned. - Strong interaction and visual design craft, with fluency in AI-assisted workflows — prototyping in code, using AI tools to explore and communicate ideas faster, and comfort working where the line between design and production is increasingly blurry. You’ll thrive as a Staff Product Designer if you: - Can hold a long-horizon systems problem and still ship focused, high-quality work in the near term. - Communicate with precision and can influence product strategy and present tradeoffs to senior stakeholders without losing the room. - Combine strong craft with the humility to test your assumptions early and often. - Stay curious and open to growth — demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact. OUR CORE BEHAVIORS - Build lasting customer trust. We build trust by taking action that puts customer trust first. - Win together. We play to win, and we win as one team. Success at Webflow isn't a solo act. - Reinvent ourselves. We don't just improve what exists, we imagine what's possible. - Own it all the way. We move fast because the moment demands it, and we hold ourselves accountable to deliver outcomes — for each other, and for customers.   BENEFITS - Ownership in what you help build. Every permanent Webflower receives equity (RSUs) in our growing, privately held company. - Health coverage that actually covers you. Comprehensive medical, dental, and vision plans for full-time employees and their dependents, with Webflow covering most premiums. - Support for every stage of family life. 12 weeks of paid parental leave for all parents and 6+ weeks of additional paid leave for birthing parents. Plus inclusive care for family planning, menopause, and midlife transitions. - Time off that’s actually off. Flexible vacation, paid holidays, and a sabbatical program to help you recharge and come back inspired. - Wellness for the whole you. Access to mental health resources, therapy and coaching. - Invest in your future. A 401(k) with 100% employer match (up to $6,000/year) in the U.S., and support for retirement savings globally. - Monthly stipends that flex with your life. Localized support for work and wellness expenses — from Wi-Fi to workouts. - Bonus for building together. All full-time, permanent, non-commission employees are eligible for our annual WIN bonus program.   Temporary employees may be eligible for paid holiday and time off, statutory leaves of absence, and company-sponsored medical benefits depending on their Fixed Term Contract and their country/state of employment.   BE YOU, WITH US At Webflow, equality is a core tenet of our culture. We are an Equal Opportunity (EEO)/Veterans/Disabled Employer and are committed https://webflow.com/diversity-equity-inclusion to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences. Employment decisions are made on the basis of job-related criteria without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other classification protected by applicable law. Pursuant to the San Francisco Fair Chance Ordinance, Webflow will consider for employment qualified applicants with arrest and conviction records.   STAY CONNECTED Not ready to apply, but want to be part of the Webflow community? Consider following our story on our Webflow Blog https://webflow.com/blog, LinkedIn https://www.linkedin.com/company/webflow-inc-/, X (Twitter) https://twitter.com/webflow, and/or Glassdoor https://www.glassdoor.com/Reviews/Webflow-Reviews-E890506.htm.   PLEASE NOTE: We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Upon interview scheduling, instructions for accommodation requests will be administered. To join Webflow, you'll need a valid right to work authorization depending on the country of employment. If you are extended an offer, that offer may be contingent upon your successful completion of a background check, which will be conducted in accordance with applicable laws. We may obtain one or more background screening reports about you, solely for employment purposes. Webflow uses AI tools to assist in screening and evaluating applications. AI does not make final hiring decisions. For details on how we process your personal information, see Webflow’s Applicant Privacy Notice https://webflow.com/legal/applicant-privacy-notice.

Location: Hybrid - San Francisco, New York City About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the role The next generation of software won’t just be used by people — it’ll be built and shipped by agents. Builds are where that happens, and they’re the beating heart of Vercel. Whether an idea starts in v0, in an agent, or in an engineer’s editor, every customer builds — and millions of builds flow through our systems every day. As an engineer on the Agentic Infrastructure team, you’ll take ownership of the systems that carry that work at scale. You won’t just contribute features — you’ll be responsible for the design, reliability, and evolution of the platform itself. You’ll make decisions that shape performance, define best practices, and ensure the workflows that Vercel, our customers, and their agents depend on are fast, resilient, and secure. This role blends product thinking with deep systems ownership. You’ll partner with teams across Vercel to build and operate the agentic infrastructure that determines how software actually ships. We’re looking for engineers who want to own high-scale systems end-to-end, thrive on improving the developer/agent experience, and are driven to have a lasting impact on how modern software gets built and delivered. What you’ll do Own and evolve the infrastructure that powers Vercel’s build and deployment lifecycle — from handling webhooks to designing resilient database schemas and building scalable APIs. Design and operate high-performance microservices that process millions of builds daily, ensuring speed, reliability, and developer delight. Lead projects end-to-end: from identifying opportunities to defining technical direction and delivering improvements in performance, reliability, and developer experience. Collaborate across teams to align infrastructure with company-wide goals and ensure seamless developer workflows. Shape the long-term vision of agentic infrastructure at Vercel by setting standards for scalability, reliability, and developer productivity. Participate in the on-call rotation, taking responsibility for the reliability of critical systems. Contribute to the open-source community, representing Vercel’s commitment to advancing developer tools globally. Write clean, efficient, tested, and well-documented code that others can build upon confidently. What you need 3+ years of experience designing, building, and operating backend applications and distributed systems at scale. Strong proficiency in JavaScript/TypeScript, with the ability to navigate and improve complex systems. Strong proficiency with cloud infrastructure (AWS) and infrastructure as code (Terraform) A track record of end-to-end ownership — from design and implementation through to long-term operation in production. Skilled at cross-team collaboration, able to influence priorities and drive alignment toward shared goals. Able to reason about technical direction and architectural tradeoffs, balancing long-term vision with pragmatic delivery. Invested in the people around you — through mentorship, code review, or simply raising the bar on how the team builds. Curious, eager to learn, and motivated to push the boundaries of how modern software gets built and shipped. Bonus if you Are familiar with React or Next.js Have experience with DynamoDB Have worked to develop a CI/CD platform or internal developer platform used by other engineers or by agents. Have experience contributing to or participating in open-source projects. Have experience optimizing build systems for monorepos or polyrepo setups. Have experience with build caching, artifact storage, or dependency management at scale. Benefits & Compensation: Competitive compensation package, including equity. Inclusive Healthcare Package. Learn and Grow - we provide mentorship and send you to events that help you build your network and skills. Flexible Time Off. We will provide you the gear you need to do your role, and a WFH budget for you to outfit your space as needed. The base pay range for this role is $196,000.00 - $294,000.00. Actual salary will be based on job-related skills, experience, and location. Compensation outside of San Francisco may be adjusted based on employee location. The total compensation package may include benefits, equity-based compensation, and eligibility for a company bonus or variable pay program depending on the role. Your recruiter can share more details during the hiring process. #LI-KR1 Disclosures: Privacy: Please review our Job Applicant Privacy Policy for more information on how we handle your data. Equal Opportunity: Vercel is committed to fostering and empowering an inclusive community within our organization. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, national origin, citizenship, age, marital status, veteran status, disability status, or any other characteristic protected by law. Vercel encourages everyone to apply for our available positions, even if they don't necessarily check every box on the job description.

Location: San Francisco, CA; New York, NY Workplace: OnSite ABOUT US Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, SoFi, Sutter Health, and SoftBank — to transform how they serve customers and grow their businesses. We are primarily an in-person company based in San Francisco, with growing offices across North America, Europe, and Asia. We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and a commitment to balancing Family along the way. These values are the foundation of our work, and we are committed to upholding them in everything we do. Our co-founders are Bret Taylor https://www.linkedin.com/in/brettaylor/ and Clay Bavor https://www.linkedin.com/in/claybavor/. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. WHAT YOU’LL DO As an Agent Strategist https://sierra.ai/blog/agent-strategist-your-phd-in-applied-ai, you own how Sierra’s AI agents come to life for our customers — from first pilot to a production agent handling thousands of conversations a day. You sit at the intersection of product, building agents and customer-facing work, and stay just as close to the technology as you are to the people you build for. You transform a customer’s thorniest, highest-stakes problems into agents that measurably move their business. - Own the Agent Development Life Cycle https://sierra.ai/blog/agent-development-life-cycle. Take agents from initial scope through conversation design, tooling, and evaluation, to launch and continuous iteration in production — translating business goals into an agent that outperforms, and tuning relentlessly until it’s the best version of itself in the real world. You’ll have real ownership and autonomy over the outcome. - Be the trusted strategic advisor to enterprise leaders. Sit shoulder-to-shoulder with our customers’ executives, understand what success actually means to their business, and shape the AI strategy that gets them there. - Partner with the customer’s working teams day to day. Run working sessions, troubleshoot the agent as issues come up, and make the calls that keep the build on track for launch. - Directly impact product. Surface unmet needs from your customer work, and feed them back to research and platform to shape where Sierra goes next. EXAMPLE PROJECTS These are the kinds of projects that strategists on our team have worked on recently: - Scope and launch a subscription-retention agent for a large telecommunications or media company that consistently outperforms human agents at saving at-risk customers. - Stand up an agent for a commerce customer that troubleshoots a broken device end-to-end and personalizes product recommendations in the same conversation. - Redesign the conversation flows for a financial services agent so it can handle complex, regulated interactions — and convert a pilot into a multi-team production deployment. See our financial services blog https://sierra.ai/blog/five-ways-to-use-ai-agents-financial-services for examples. - Partner with product on a net-new capability — a new agent architecture or self-service tooling — using a live customer as the design partner. - Define the evaluation and quality bar for a new agent, then use those metrics to drive a measurable lift in outcome https://sierra.ai/blog/outcome-based-pricing-for-ai-agents week over week. WHAT YOU’LL BRING - Customer obsession. Genuine energy being in front of customers — understanding their business and needs, thriving in complex organizations, and building trusted relationships. - Communication. Clear, direct, and persuasive across technical and non-technical audiences. - Strategic problem-solving in ambiguity. Strong analytical and critical-thinking skills to break down complex problems, spot risks early, and adapt as things change fast. - Technical aptitude. Comfortable engaging directly with technical concepts - reading API documentation, understanding data models and system architecture, and following engineering tradeoffs in a design discussion. - Ownership and delivery. A track record of running multiple complex, high-visibility projects at once and driving them to outcomes. - Genuine interest in Financial Services and improving the end customer experience. Experience in financial technology, implementations at financial institutions, working inside of these institutions or familiarity with financial services security and compliance requirements (fair lending, PII handling, etc.) are a strong plus. EVEN BETTER... - Experience building or deploying AI/LLM agents in production — hands-on with the tools behind them (eval frameworks, agent tooling, RAG, prompt engineering) — working closely with technical counterparts. - You’ve been a founder, founding team member, or operator — you know how to balance craft, ownership, and speed. - A degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience — and/or an MBA or comparable experience at the intersection of technology and business. OUR VALUES - Trust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work. - Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it. - Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve. - Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time. - Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements. WHAT WE OFFER We want our benefits to reflect our values and offer the following to full-time employees: - Flexible (unlimited) paid time off - Medical, dental, and vision benefits for you and your family - Life insurance and disability benefits - Retirement plan dependent on country of employment - Parental leave - Fertility and family building benefits through Carrot - Lunch, as well as delicious snacks and coffee to keep you energized  - Discretionary benefit stipend giving people the ability to spend where it matters most - Free alphorn lessons These benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies. BE YOU, WITH US We're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

Задачи: — Проектировать и создавать AI-агентов и решения на базе больших языковых моделей (LLM) — Разрабатывать конвейеры данных и lakehouse-решения в Databricks — Интегрировать AI-агентов с Databricks и другими платформами данных — Создавать решения на Python для сбора данных, веб-скрапинга и индексирования контента — Вносить вклад в архитектуру и технические решения — Тесно сотрудничать с международной инженерной командой Требования: — Опыт работы на уровне senior в области разработки ПО или AI-инженерии — Уверенное владение Python — Практический опыт работы с GenAI, LLM и Agentic AI — Опыт работы с инженерией данных и конвейерами данных — Практический опыт работы с Databricks — Способность брать ответственность и участвовать в архитектурных решениях — Владение английским языком на уровне C1 Будет плюсом: — Знание графов знаний и онтологий — Опыт веб-скрапинга — Знание Databricks Genie — Опыт работы с агентскими фреймворками и разработкой с нуля архитектуры Условия: — Медицинская страховка — Более 21 дня отпуска — Возможности профессионального развития — Поддержка карьерного коуча Проект международный, европейское сотрудничество, локация Ташкент, Узбекистан.

Задачи: — развивать и рефакторить оркестрацию агентов на LangGraph — разрабатывать скиллы и инструменты (tools) для агента — интегрировать LLM (писать и оптимизировать system/user-промпты, проектировать Pydantic-схемы для структурированного вывода, настраивать параметры моделей) — подключать внешние системы (HTTP API, Kafka, поисковые движки) — строить RAG-пайплайн — покрывать код unit-тестами — участвовать в проектировании архитектуры агентских систем. Требования: — опыт разработки AI агентов от 1 года — опыт разработки python от 3 лет — опыт с веб-фреймворками (FastAPI и/или aiohttp) и проектировали REST API; опыт работы с WebSocket/SSE для real-time коммуникаций — опыт интеграции LLM через API (GigaChat, аналоги) — опыт с LangGraph/LangChain или похожими оркестраторами агентов — опыт с PostgreSQL (проектирование схем, миграции, транзакции) и асинхронным доступом к БД — умеете доводить LLM-фичи до стабильной работы в проде. Будет плюсом: — опыт работы с AEF — опыт с RAG — опыт с Kafka и событийными интеграциями — опыт работы с Docker / Kubernetes, Helm, CI/CD пайплайнами — навыки работы с генеративными AI-моделями — опыт создания AI-агентов и использования их в работе будет преимуществом — опыт использования GigaChat, Kandinsky и аналогов в продуктах, навыки создания и использования AI-агентов — инструментальное владение AI для анализа, генерации и автоматизации. Условия: — гибридный формат работы (2-3 дня в офисе). Офис по адресу: г.Москва офис Кутузовский проспект 32 — ежегодный пересмотр зарплаты, квартальная и годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.

Задачи: — Определять, где могут помочь AI агенты, и создавать их соответственно. — Работать с руководителями отделов для оценки потребностей в AI. — Помогать подключать агентов к соответствующим сторонним и внутренним инструментам. — Измерять результаты и удалять агентов, которые не приносят пользы. — Тестировать новые инструменты и модели по мере их появления и внедрять эффективные. — Консультировать других по возможностям AI для повышения их эффективности. Требования: — Опыт создания агентов, которые работают самостоятельно и выполняют значимую работу. — Хорошее знание Grok, Claude, OpenAI и open source. — Уверенное владение Go, TypeScript, GraphQL, Postgres, GCP. — Способность ясно писать на английском языке. Условия: — Зарплата от $150,000 до $250,000 в год. — Подписной бонус $20,000. — 4 недели отпуска плюс праздничные дни по стране. — Полностью удалённая работа.

Задачи: — Разрабатывать повторно используемые паттерны для агентных сервисных рабочих процессов, оркестрации, протоколов HITL, логики переопределения и эскалации, механизмов обеспечения качества, чтобы разработчики могли собирать решения из проверенных компонентов — Устанавливать стандарты, которым следуют разработчики, достаточно конкретные для применения без вашего участия — Избирательно прототипировать рабочие процессы для проверки паттернов, выявления пробелов или решения сложных задач, затем выделять повторно используемые части и передавать их — Внедрять полученные знания из каждого проекта обратно в общие паттерны для повышения скорости и безопасности — Влиять на продуктовую команду, формируя приоритеты и конкретные запросы на разработку, основанные на данных и опыте разработчиков — Прототипировать решения для пробелов в платформе, доказывая необходимость их создания — Оценивать возможности автоматизации по объему, риску и влиянию на клиента, используя SOP, операционные метрики и данные взаимодействий — Работать с командой данных для определения метрик производительности рабочих процессов — Определять процессы, которые не должны быть автоматизированы — Обеспечивать качество, включая участие в юридических, безопасностных и комплаенс-ревью, чтобы требования были заложены в паттерны — Представлять результаты портфеля старшим заинтересованным сторонам кратко и эффективно Требования: — Более 8 лет опыта в операциях, продукте или AI, включая минимум 2 года в проектировании и внедрении AI-поддерживаемых или агентных рабочих процессов в продакшене — Практический опыт работы с агентными инструментами, оркестрационными фреймворками или интеграциями MCP, включая координацию нескольких агентов — Глубокое понимание LLM-систем: дизайн запросов, оценка и поведение моделей в масштабе — Опыт проектирования систем с участием человека в цикле, с четкой логикой эскалации, контролем переопределения и соблюдением требований — Умение определять и анализировать метрики рабочих процессов (уровень решения, сдерживание, качество эскалации) и отличать реальные регрессии от шума — Успешный опыт влияния на продукт, инженерные, юридические, безопасностные и комплаенс-команды в письменной форме, на дизайн-ревью и в важных форумах — Знакомство с практиками ответственного AI, управлением и управлением рисками в продакшене — Опыт работы в условиях активного переопределения функций Желательно: — Опыт с архитектурами RAG и оптимизацией качества поиска — Способность оценивать данные, качество и управление для поддержки надежной агентной работы — Опыт работы в SaaS, финтехе или регулируемых средах с реальными ограничениями комплаенса — Знакомство с процессами AI-управления или обзором безопасности Условия: — Годовая зарплата от $168,420 до $210,525 для Денвера и большинства крупных городов, от $197,895 до $247,369 для Сан-Франциско и Нью-Йорка — Гибридный формат работы с офисами в Денвере, Сан-Франциско и Нью-Йорке, ожидание присутствия в офисе 2-3 дня в неделю — Требование надежного и безопасного интернет-соединения при работе вне офиса — Компания предоставляет конкурентную базовую оплату, льготы и акции (RSU) — Равные возможности при найме и поддержка кандидатов с инвалидностью

Задачи: — Разработка Co-Pilot решений (RAG + LLM) и микросервисов в качестве MCP-инструментов. — Проектирование и интеграция AI-агентов, Code Review и менторство. — Участие в Scrum-процессах и проектировании архитектуры. Требования: — Коммерческий опыт на Python — от 4 лет. — Опыт внедрения AI-агентов в пром (LangChain, LangGraph). — Микросервисы, асинхронный Python, SOLID, PostgreSQL, Unit-тесты. Будет плюсом: — DDD, Kafka, Qdrant, OpenSearch. — Навыки Vibe Coding, промпт-инжиниринга и AI-ассистентов (Cursor, Copilot).

Location: Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As Director, Product Management: Agentic Software Delivery, you'll own one of GitLab's most strategic sections, spanning Continuous Integration, Artifact Management, Continuous Deployment, and Observability. You'll lead senior and principal product managers and be accountable for adoption, retention, and revenue across build, package, deploy, and monitor. Today, these are separate stages with a human making the call at each handoff. As agents take on more coding, pipeline, and deployment work, you'll set the three-year vision for how much of that judgment the system can make safely and how quickly a production signal can turn into a fix without waiting for a human to notice it first. You'll define how customers move from today's manual checkpoints toward agent-driven software delivery at a pace that fits their risk tolerance. In your first year, you'll bring four connected roadmaps into one coherent strategy, establish how investment is allocated and reallocated, deepen partnerships with Engineering and go-to-market leaders, and give customers a credible path for managing software delivery at scale. What you’ll do Own the strategy, three-year vision, and business outcomes for GitLab's Agentic Software Delivery section, with a clear point of view on how artificial intelligence is changing software delivery. Lead and develop senior and principal product managers across Continuous Integration, Artifact Management, Continuous Deployment, and Observability, helping them grow as independent decision-makers. Establish the frameworks, standards, and operating rhythm that support consistent, high-quality product decisions without unnecessary escalation. Own section-level key performance indicators and adoption funnels, using the results to reallocate investment or stop work that isn't paying off. Evaluate major strategic bets, partnerships, and build, buy, or partner decisions, and develop the business cases that support them. Partner with Engineering leadership on platform investment, architectural direction, and trade-offs across the section, while connecting build, package, deploy, and monitor into one coherent customer experience. Drive pricing, packaging, go-to-market strategy, migration, and adoption with Product Marketing, Sales, Pricing, Customer Success, and Solutions Engineering across free, commercial, and enterprise offerings. Represent the section with GitLab's senior leadership, key enterprise customers, partners, and industry audiences, while modeling AI-native product management across discovery, synthesis, prototyping, roadmap exploration, and concept development. What you’ll bring Experience leading product managers, including developing senior and principal talent, hiring, and addressing performance directly. A track record of owning a portfolio across multiple product areas and being accountable for adoption, retention, and revenue, not only roadmap delivery. Product management depth in one or more relevant areas, such as continuous integration and continuous delivery pipelines, artifact or package management, release management, or observability. Sound judgment about where to invest and where to stop, including experience making and defending build, buy, or partner decisions with a business case. Technical fluency to work with engineers and architects on pipeline design, artifact workflows, deployment strategies, and observability signals such as logs, metrics, and traces. Experience shaping pricing and packaging for technical products across free, commercial, and enterprise offerings. Experience working with technical customers in developer tools, DevOps, or software delivery environments where engineers and engineering leaders are primary users. Executive-level communication and influence. Practical use of AI tools in product management workflows, along with a thoughtful view of how AI and agentic workflows are changing software delivery. We welcome candidates whose experience may come from different but transferable product and leadership paths. About the team The team brings together senior product leaders across GitLab's software delivery platform and works closely with Engineering, Design, and go-to-market partners so customers experience these capabilities as one connected system. The team helps customers manage today's delivery complexity while shaping how AI-powered and AI-native workflows influence the next generation of software delivery. As part of GitLab's all-remote organization, the team collaborates asynchronously across regions with a focus on transparency, written communication, and clear decision-making. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $203,200 — $345,600 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: United States; Canada Workplace: Hybrid WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ROLE OVERVIEW Ready to build AI agents that revolutionize enterprise security? The North Security team is looking for a Senior Software Engineer to create autonomous systems that handle the complex, critical tasks security practitioners face every day. KEY RESPONSIBILITIES As a Senior Software Engineer focused on agentic security, you'll build intelligent systems that empower security teams. Your responsibilities will include: - Build autonomous security agents that perform alert triage, secure code reviews, threat modeling, and vulnerability assessment - Develop agent orchestration systems that help security practitioners automate repetitive security tasks - Design and implement agent security controls to ensure our AI agents can safely interact with sensitive enterprise data - Create the security infrastructure that allows agents to operate in high-trust environments with stringent deployment requirements - Ship production-ready agent capabilities that run efficiently in resource-constrained environments - Research and implement novel security patterns for AI agent systems, sometimes requiring custom solutions where standard libraries fall short - Conduct security testing of both the agents you build and the platform that runs them. QUALIFICATIONS - 5+ years of software engineering experience with a track record of shipping user-facing security features - Strong Python development skills with significant production experience - Experience building or working with autonomous systems, AI agents, or intelligent automation - Solid understanding of security principles including session management, authentication, authorization, and secure coding practices - Ability to think about security at multiple layers: application security, agent behavior security, and infrastructure security - Comfortable working across the full stack and diving into unfamiliar codebases to understand and fix issues - Thrive in fast-paced environments where you can adapt to evolving priorities - Excited about the intersection of AI/ML and security engineering. WORKING LOCATION This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role. FULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS: - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. Education & learning stipend for conferences, courses, and coaching. - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. HOW AND WHERE WE WORK: - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly. If any of the above doesn’t line up exactly with your experience, we still encourage you to apply. We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process. All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias. If jobs are viewed on other sites then please verify these through our official careers https://cohere.com/careers page.

Задачи: — расширение клиентской базы — увеличение дохода — выявление новых возможностей для развития бизнеса Требования: — свободное владение английским языком — подтверждённый опыт в продажах с сильными навыками ведения переговоров и закрытия сделок — технические навыки письма, устного общения и межличностного взаимодействия — знание финансовых рынков — самомотивация, динамичность и ориентация на поддержку клиентов Условия: — базовая зарплата €2,500 брутто + высокие бонусы и лучшие стимулы — рабочие часы с 10:00 до 19:00 с акцентом на баланс между работой и личной жизнью — доступ к высококачественной базе клиентов (только горячая база) — 21 день ежегодного отпуска, ежедневные офисные закуски и напитки — мероприятия команды, призы и возможности профессионального роста — виза не предоставляется

Задачи: — расширение клиентской базы — увеличение доходов — выявление новых возможностей для развития бизнеса Требования: — свободное владение английским языком — подтверждённый опыт продаж с сильными навыками ведения переговоров и закрытия сделок — технические навыки письма, устного общения и межличностного взаимодействия — знание финансовых рынков — самомотивация, динамичность и ориентация на поддержку клиентов Условия: — базовая зарплата €2,500 брутто + высокие бонусы и лучшие стимулы — рабочие часы с 10:00 до 19:00 с акцентом на здоровый баланс работы и личной жизни — доступ к высококачественной базе клиентов (только горячая база) — 21 день ежегодного отпуска, ежедневные офисные закуски и напитки — мероприятия команды, призы и возможности профессионального роста — виза не предоставляется

Location: Remote, Canada; Remote, Poland; Remote, United Kingdom; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. About the role We are looking for a Principal Engineer to help build GitLab Duo Agent Platform, the agentic orchestration layer that runs AI agents and flows across the entire software lifecycle. Principal Engineers at GitLab are recognized experts across multiple technology domains and represent the senior technical leadership within their organization. In this role you will set technical direction for a significant part of the Agent Platform, working across several teams to turn agentic capabilities into something engineering organizations can actually depend on: predictable, observable, governable, and fast enough to sit in the critical path of real development work. The Agent Platform is not a single service. It spans agent execution and orchestration, flow definition and event-driven triggering, the AI Catalog through which customers discover and manage agents, model routing and evaluation, and the governance surface that decides which agents may act where and under whose identity. It runs on GitLab.com, GitLab Dedicated, and Self-Managed installations, including deployments that use self-hosted models to meet compliance requirements. You will work on the parts of that system where the hard architectural questions live, and you will do it hands-on. This role reports into the VP of the AI Engineering organization and works closely with Engineering Managers, Staff Engineers, Product Management, Infrastructure and Security. What you'll do Define the technical direction for a significant area of Duo Agent Platform across several teams, and partner with Engineering Managers and Product to turn it into a roadmap with a six-month horizon. Build the orchestration layer that makes agents and flows reliable: session lifecycle, tool invocation, context assembly, concurrency, retries, timeouts, and failure modes that degrade gracefully instead of stalling a developer's workflow. Hands on work on driving topics throughout the whole organisation from POC level, architecture to full implementation. Participate in Incident Management on-call rotation, to help meet availability goals for GitLab.com. Strong product builder and ownership mentality. Understanding of product strategy, technical strategy, delivering customer value and iteration towards a successful product Write clear, opinionated design documents, architecture narratives, and decision records that let other teams make aligned decisions. Ensure the architecture holds across multi-tenant GitLab.com, Dedicated, and Self-Managed deployments, including self-hosted model configurations, and respects data governance boundaries in each. Use the platform on our own work, find where it falls short of what we claim, and feed that back through improvements into the product. Mentor Staff and Senior Engineers, and raise the bar for experimentation rigor and cross-team collaboration. Work across the whole platform on different projects, features and teams. This reaches across: Design the extensibility surface so customers can build custom agents and flows, connect their own tools and internal systems, and bring external agents such as Claude Code and Codex into GitLab workflows without weakening the platform's guarantees. Drive down the cost and latency of agentic requests, and work with Product on how model selection, routing, and credit consumption behave as usage grows. Define the evaluation practice for the platform: offline benchmarks and online experiments that measure task completion, correctness, tool-call accuracy, latency, and cost per task, and that catch regressions before customers do. Build the governance and safety surface with Security and Compliance: policy-driven controls over which agents and models may run where, permission and identity semantics that align to existing roles and group structure, human-in-the-loop checkpoints, traceability of every flow session, and audit that stands up to enterprise review. Complete Interview Training and participate in hiring for the department as a technical interviewer or panel member. What you'll bring 8+ years of software engineering experience, including 3+ years at Staff, Principal level or equivalent senior technical leadership. Hands-on production experience building on large language models: agent loops, tool calling, context management, retrieval, prompt and model evaluation. Experience shipping this to real users, not only prototyping it. Strong background in distributed systems, including service decomposition, fault tolerance, observability, and operational resilience under multi-tenant load. A track record of defining evaluation frameworks and using benchmark and experiment results to make architecture decisions, rather than shipping on intuition. Experience designing human-in-the-loop controls, safety guardrails, and responsible AI practices for systems that act on a customer's behalf. Ability to drive alignment across Engineering, Product, Infrastructure, and Security on problems that start out ambiguous. Experience mentoring senior engineers and shaping technical direction across multiple teams without direct authority. Comfort working in one or more of Ruby, Go, Python, or TypeScript, and willingness to work across the stack the platform spans. Excellent written and asynchronous communication, and the ability to work effectively in a fully remote, globally distributed organization. About the team The AI engineering organisation is building the product and infrastructure that make GitLab an effective environment for running agents across the software development lifecycle. We’re distributed across the world and partner with teams throughout GitLab to help the GitLab Duo Agent Platform become the backbone of GitLab's AI features. You will report directly to the VP of Engineering for AI and especially work together with all the teams, the engineering management and other principal engineers in the AI department. This is an opportunity to lead a consequential group as AI changes how software is built. The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $250,000 — $325,000 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Location: Limassol; Nicosia; Athens; Thessaloniki; Fully Remote - in other eligible locations Workplace: hybrid The Role:  We're seeking a Senior AI QA Test Automation Engineer to take a leading technical role in AI quality and test automation. You will work primarily with our AWS Bedrock AgentCore-based CX Agent Suite, a multi-agent customer-support system covering intent routing, FAQs, deposit-status queries, and human handoff. You will design and build the evaluation and QA tooling required to validate AI agents reliably, while also contributing to technical standards and best practices across QA.  This is a Senior Individual Contributor (IC) role with a strong technical and strategic focus. You'll work closely with QA leadership, Data Science, and Engineering to architect scalable AI evaluation systems, establish technical standards, and drive the evolution of our AI evaluation framework. Our current evaluation harness is based on DeepEval and is evolving towards a broader agentic evaluation architecture. You will have the opportunity to evaluate and prototype emerging agent-orchestration approaches, including Strands Agents, and contribute to architectural decisions around their adoption. The main responsibilities of the position include: Act as the primary technical enabler for QA, building scalable AI/ML frameworks, libraries, and tooling for the CX Agent Suite and beyond Design and build AI evaluation pipelines that assess the CX Agent Suite's multi-agent responses (Intent Detector, FAQ Agent, Missing-Deposits Agent) for accuracy, relevance, tone, hallucination rate, safety/guardrail compliance, and task completion — extending or replacing the current DeepEval-based evaluation harness Evaluate and prototype Strands Agents (or comparable agent-orchestration frameworks) for building self-evolving, autonomous QA agents, and drive the go/no-go decision on adoption Collaborate with QA, Data Science, and Engineering to integrate AI-driven testing into the existing GitLab CI/CD pipeline (dev → test → staging → prod), alongside Terraform-provisioned, EKS/AgentCore-hosted services Build resilient and adaptive automation that can detect and respond to changes in agent behavior, Bedrock Guardrails configuration, and routing logic Develop data-driven quality analytics, including root-cause analysis, quality trends, and intelligent test prioritization, leveraging existing observability and evaluation data from OpenTelemetry, CloudWatch, X-Ray traces, and LangFuse offline evaluation runs Lead research into emerging AI testing methodologies and mentor engineers through code reviews, workshops, and architectural guidance Main requirements: BSc/MSc in Computer Science, AI, or a related discipline 6+ years of hands-on experience in QA/Test Automation, with strong experience designing and maintaining automation frameworks 1+ years of experience applying AI/ML in software testing or QA process improvement, with a proven track record of bringing AI/ML solutions into production workflows Strong Python skills, with experience working in Python/AWS-centric technology environments; Java and/or TypeScript is a plus Hands-on experience with LLM evaluation techniques, including LLM-as-a-judge, human-in-the-loop evaluation, RAG, and multi-agent orchestration patterns Practical experience with DeepEval or comparable evaluation frameworks, along with familiarity with agent-orchestration SDKs such as Strands Agents Knowledge of LLM tooling, vector databases, and MLOps pipelines Experience integrating AI tooling into enterprise CI/CD environments, particularly GitLab, and working with containerized cloud-native environments such as Docker and Kubernetes/EKS Strong communicator, able to influence technical decisions and drive engineering standards across teams The following will be considered an advantage: Experience with autonomous QA agents or agentic orchestration frameworks for self-evolving test suites Experience with LLM observability tools such as LangFuse, LangSmith, or Arize, particularly for measuring probabilistic and adversarial robustness Knowledge of AI ethics, fairness, and bias detection for guardrail and model validation Experience with gRPC, WebSockets, and/or HTTP/2 Experience with AWS Bedrock, plus familiarity with GCP Vertex AI and/or Azure AI Benefit from: Attractive remuneration package Intellectually stimulating work environment Continuous personal development and international training opportunities The Hiring Experience: What Awaits You Let’s Connect – Intro Chat with Talent Acquisition Deep Dive – First Interview with Your Future Team Final Connection – Final Interview All applications will be treated with strict confidentiality!   By submitting this application, I confirm that I have read and agree to the terms of the Privacy and Data Protection Notice and the Confidentiality Undertaking.

Location: San Francisco; New York City Perplexity Computer is one of the defining products of the new era of agentic AI. Millions of people use Perplexity to transform knowledge into action, and the Agent Capabilities team sits at the intersection of frontier AI research and product innovation, building the foundations that shape how users and agents solve increasingly complex tasks. As every major breakthrough in AI models creates new possibilities, the Agent Capabilities team is responsible for turning frontier AI breakthroughs into reusable product capabilities. We are often the first to evaluate emerging model capabilities, determine where they create real user value, and transform them into reliable, scalable, high quality experiences for both users and agents. This is a highly leveraged role with broad ownership at the intersection of frontier AI research, agent systems, platform engineering, and product innovation. Tech Stack: Python | Go | Rust | PostgreSQL | DynamoDB | AWS | TypeScript WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Evaluate frontier models against real user tasks, identify useful behaviors and failure modes, and turn the most promising advances into production agent systems. Own the lifecycle from rapid prototyping and evaluation through launch, monitoring, and iteration. - Improve agents’ ability to plan, use tools, manage context, recover from errors, and complete long-running tasks reliably. - Apply state of the art ML and LLM techniques to design scalable agent capabilities such as skills, plugins, artifact generation, tools integrate and use, auto-research, and multi-agent collaboration. Shape the architecture, abstractions, and product experiences that enable both users and agents to compose increasingly sophisticated solutions for real-world tasks. - Own agent behavior and capabilities end-to-end, from user-facing products and interfaces to backend services. Define offline and online evaluations for task completion, correctness, safety, latency, cost, and user satisfaction. Iteratively improve across models, prompts, harnesses, and products for different problem spaces. - Build secure, observable, and reliable agent systems, including permissions and safeguards for sensitive actions. Develop tracing, replay, and monitoring infrastructure that makes agent failures reproducible and actionable. - Collaborate closely with PM, Data Science, Research, to identify high-impact opportunities in understanding and validating emerging model capabilities, and turn complex agent behaviors into simple, reliable product experiences. - Apply relevant advances in models, inference, evaluation, and agent architecture when they produce measurable improvements in production performance. Set technical direction on ambiguous problems and raise the bar through design reviews, mentorship, and technical leadership. QUALIFICATIONS - Typically 6+ years of professional software engineering experience, with a track record of building and owning robust AI-powered, large-scale, user-facing or data-intensive products. Exceptional candidates with less experience and an outstanding record of impact are encouraged to apply. - Strong software engineering fundamentals, with experience building and operating AI/ML products, backend services, or distributed systems at scale. - Experience owning the AI product lifecycle, including data analysis, rigorous evaluation, production monitoring, and iterative improvement. Able to define metrics and use production data and user feedback to guide decisions. - Practical experience in one or more relevant areas, such as agent harnesses, tool use, context engineering, model evaluation, browser automation, or long-running task execution. - Strong product judgment and execution: you can translate ambiguous user needs into applied AI or ML problems and ship durable solutions with measurable user impact. - Genuine interest in frontier AI capabilities, agent systems, and excitement for rapidly exploring, evaluating, and productizing new model behaviors. NICE TO HAVE - Experience with LLM context engineering or harness engineering, experience with subagents, coding assistants, long-running or autonomous task execution. - Deep familiarity with the strengths and limitations of current model families across reasoning, tool use, context management, and long-horizon tasks. - Experience building agent permissions, safeguards, evaluation infrastructure, or production observability systems. - Experience with mid-training, post-training, or reinforcement learning for frontier or open-source models, along with a strong understanding of model strengths and limitations across reasoning, tool use, context management, and long-horizon tasks. - AI/ML research experience demonstrated through publications, open-source contributions, or other meaningful research impact. - Time spent at a fast-growing startup or on a high-ownership engineering team.

Location: Remote Who we are Our mission is to bring clarity and control to the world's most complex codebases. AI is accelerating code creation, but the infrastructure to understand, oversee, and evolve that code hasn't kept pace. Sourcegraph gives engineering organizations full visibility across their systems, precise context for their agents, and the ability to execute coordinated code changes at scale. As agentic development becomes the dominant engineering paradigm, we provide the context layer teams need to take control of their codebase. With Code Search, Deep Search, MCP, and Agentic Batch Changes, we deliver on that mission today - giving engineering teams and their AI tools the cross-repo context to navigate massive codebases with confidence, and the ability to make changes across hundreds of repositories at once. Companies like Stripe, Reddit, and Leidos rely on Sourcegraph to ship faster and with higher quality. We're backed by a16z, Sequoia, and Redpoint, and proud to operate as a globally distributed team that values high agency, direct communication, and customer love. If you want to build the infrastructure that lets every engineering team - and every agent they deploy - operate on their codebase with confidence, join us. Hours & location 🌎 While we hire almost anywhere in the world, we have a preference for someone to reside in the following locations for this role. However, if you feel qualified, we welcome you to apply regardless of location. No matter what, working hours must overlap with EST for at least 20 hours/week. Preferred locations: USA Why this job is exciting Sourcegraph is at the forefront of building AI tools to solve the biggest problems in the software industry, problems that only get bigger as codebases grow and as more of the work is done by agents. The Code Understanding team owns the surfaces where that intelligence meets the developer: Deep Search , our agentic, multi-step answer engine across an enterprise's entire lineup of codebases, Query Assist , turning natural language queries into Sourcegraph query syntax, Smart Hovers , concisely summarizing symbols right where devs need it, guided diff review, and the APIs that both humans and AI agents rely on every day. Most of what makes those surfaces tick is agent engineering : a blend of software engineering, machine learning, and statistics. Agent engineering tells us which model to use and when, how to retrieve and pack context, how to measure answer quality, where to fine-tune or distill a smaller model to cut costs and latency, and how to expand a single LLM call into a reliable multi-step agent. As the staff ML and agent engineer on Code Understanding , you'll be the technical owner of it: setting the tam’s direction for models, evaluations, and agentic systems, making our products measurably better, faster, and cheaper, and raising the team's fluency in building with models. This is a staff-level role : we're hiring a technical leader, not just a strong individual contributor. The primary need is a production ML and evaluation authority who also builds production agent systems. You'll own the hardest, most ambiguous problems in this space, set standards others follow, and influence direction beyond your immediate team. You'll get the exhilarating chance to drive the vision on how we can provide the best code understanding experience on the market by combining our deterministic, large-scale systems and AI into experiences never seen before. Concretely, you'll own work like: Agentic systems. You'll design and harden the multi-step, tool-using agent loops behind current and new agentic experiences, turning research and experiments into reliable, observable, and affordable products at enterprise scale. Pragmatic use of evaluations. Crafting agentic products means needing to tell when a change actually helped, which is hard when agents keep changing and the product keeps shifting. You'll bring judgment about where evaluations earn their keep, when to use targeted smoke tests and metrics, and how to avoid noise dressed up as rigor, so we can move fast with confidence. Models: selection, upgrading, and training. You'll decide which models we run where, drive upgrades, and fine-tune our own when that's the right call. Retrieval and context engineering. You'll push on how we ground models in a customer's code - retrieval, ranking, context windows, citations - to make answers more accurate and verifiable. Cost and latency. Every surface has a per-user economic budget. You'll treat cost and latency as product features, and profile, distill, cache, and right-size models so we can ship ambitious features sustainably. You'll do this on a small, senior-leaning team that ships quickly, owns a lot of product surface, and has streamlined product management: engineers here talk to customers, frame the problem, and own it end-to-end. You'll have real agency over technical direction and a direct line to the impact of your work. 📅 Within one month, you will… Get the Code Understanding products and their model/agent pipelines running end-to-end locally, and land your first improvements to a model, prompt, retrieval path, or eval. Build a clear picture of where the AI engineering pain is, and the product surfaces most constrained by them. Get to know the team and our customers, and start forming your own opinions about where our agentic products should go next. Join the team's on-call support rotation. 📅 Within three months, you will… Own a meaningful agentic slice of the product end-to-end, driving it from problem-framing through rollout and measurement. Establish how the team ships model and prompt changes responsibly: the evals, dashboards, and guardrails that make quality and cost regressions visible before customers feel them. Begin up-leveling teammates in building with models by pairing with them, reviewing their code, and modeling good agent engineering instincts. 📅 Within six months, you will… Be the recognized technical authority for agent engineering and agentic systems on Code Understanding. You will be the person teammates, and increasingly the wider department, defer to on model, eval, and agent-design decisions. Have measurably moved the products: better answer quality, lower cost/latency, or new agentic capabilities that weren't feasible before. Be setting the direction of the team's roadmap where it intersects agents, bringing conviction, backed by evidence, about which bets are worth making, and pulling other engineers up to execute on them. About you You are a staff engineer and technical leader with hard-won skills across production machine learning, evaluation, and agent systems . This high-leverage role relies on your ability to make sound model and evaluation decisions for a fast-moving product, build the production systems around them, steer technical direction, and be a force multiplier for a talented, product-minded team. You're equally comfortable reasoning about an eval harness, a fine-tuning run, a retrieval pipeline, and the multi-step agent loop that ties them together, and you make everyone around you better at all of it. You operate at staff scope: you own the most ambiguous, highest-risk problems in your domain, go into whatever codebase a problem requires, set standards and patterns others adopt, and translate fluidly between engineering goals and business objectives. You influence direction beyond your immediate team. You lead through technical excellence and mentorship. You have personally owned a production model lifecycle. You have trained or fine-tuned at least one model and taken it from dataset construction through evaluation, production rollout, and monitoring. You can explain how you chose between training or fine-tuning and prompting or retrieval, how you chose baselines and metrics, what error analysis revealed, and how production evidence affected the next version. You build agents, fluently and opinionatedly. You've designed multi-step agentic systems and made them reliable, observable, and cost-bounded. You have a point of view on where agents shine and where deterministic code or human judgment is required. You have strong evaluation judgment. You build representative datasets, meaningful baselines, useful error taxonomies, and release criteria that connect offline measurements to production behavior. You know where rigorous evaluations earn their keep, where lightweight smoke tests or qualitative review are enough, and where a precise-looking metric is misleading. You treat cost and latency as product constraints. You make measured quality, latency, and cost tradeoffs and use the appropriate combination of model selection, prompting, retrieval, caching, distillation, and fine-tuning rather than reaching reflexively for a more complex model. You operate autonomously on ambiguous problems. Given a rough product idea, a few customer quotes, and a Slack thread, you come back with a plan, a prototype, milestones, and a point of view on tradeoffs, without it being pre-scoped. You own high-technical-risk projects end-to-end. You contribute beyond your domain. As a senior IC, you go into whatever part of the codebase a problem requires, recognize issues beyond your immediate area, and translate between engineering goals and business objectives. You up-level the people around you. You mentor by pairing on hard problems, providing substantive design and code reviews, and spreading agent engineering literacy across the team. You see investing in your teammates' growth as part of the job. You're customer and product-driven. You're comfortable on customer calls and in feedback threads, you turn raw signals into requirements, scopes, and milestones, and you push back when feedback would lead the product astray. You're pragmatic, not a perfectionist. You ship the smallest correct thing, prefer robust solutions over complicated ones, and keep a high-quality bar with simplicity. On the engineering fundamentals: You're a strong software engineer who can ship production services. You're comfortable across our stack - Go on the backend, TypeScript on the frontend, GraphQL, Postgres, Docker - or you're clearly able and eager to get there. You're fluent with agentic coding tools, and you understand and own every line it submits. You're comfortable in an async-first, multi-service, fast-paced remote environment. Nice-to-haves: You've shipped an LLM-powered or agentic developer-facing product you can speak about opinionatedly: what worked, what didn't, what you'd do differently. You've fine-tuned, distilled, or trained models to meet cost, latency, or quality targets in production. Experience with retrieval, ranking, embeddings, or search relevance. Experience working directly with enterprise customers and translating their needs into a product. Experience mentoring or up-leveling engineers, especially raising a team's agent engineering fluency. Level 📊 This job is an IC4. You can read more about our job leveling philosophy in our Handbook. Compensation 💸 We pay above-market salaries because we want to hire exceptional people who can focus on building great products, not worrying about paying bills. As an open and transparent company, our compensation philosophy and pay bands are visible to every Sourcegraph teammate, and we strive to make our approach equitable, explainable, and competitive. Your base salary is determined by the IC4 pay band for your location zone (1-4). Our pay bands are informed by market data and designed to ensure competitive compensation wherever you live. During the recruiting process, we'll discuss the range applicable to you based on job level, relevant skills, experience, qualifications, and location zone. 💰 The starting salary for the IC4 pay band in each zone is: Zone 2: $176,000 USD Zone 3: $132,000 USD Zone 4: $88,000 USD 📈 In addition to competitive cash compensation, we offer meaningful equity (because when Sourcegraph succeeds, we want you to succeed, too) and generous perks & benefits . Interview process Below is the interview process you can expect for this role (you can read more about the types of interviews in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all! We expect the interview process to take 5.5 hours in total. 👋 Introduction Stage - we have initial conversations to get to know you better… [30m] Recruiter Screen [30m] Hiring Manager Screen 🧑‍💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team, including cross-functional partners… [60m] Resume Deep Dive [60m] System Design [60m] Harden a Code Research Agent Interview [60m] Cross-functional team collaboration / Values 🎉 Final Interview Stage - we move you to our final round, where you gain a better understanding of our business and values holistically… [30] Leadership We check references and conduct your background check Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process. Learn more about us You can learn more about what it is like to work at Sourcegraph by reading our handbook . We are an ambitious team who are collectively working hard to build the most influential company in the world. You can read more about our culture , competitive compensation and benefits here. Sourcegraph is an equal opportunity workplace; we welcome people from all backgrounds. Sourcegraph participates in E-Verify for U.S. Employees.