AI-инженер (LLM, агенты, AI product) вакансии

TypeSafe ищет специалиста по безопасности для работы в офисе в Сан-Франциско. В обязанности входит разработка методов оценки моделей, анализ нежелательного поведения моделей, выявление потенциальных проблем и документирование результатов исследований. Кандидат должен иметь опыт в области безопасности ИИ, интерпретируемости моделей и проведения исследований, связанных с оценкой и выравниванием моделей.

Sierra is looking for a Strategist in Agent Development for Travel Transportation and Hospitality. Задачи: — Разрабатывать и запускать AI агентов — Консультировать корпоративных клиентов Требования: — Опыт работы с AI, системной архитектурой, API, prompt engineering, data model, RAG, conversation design, evaluation Условия: — Работа в офисе в Сан-Франциско — Зарплата от $200,000 до $290,000 в год

Sierra is looking for a Cantonese Speaking Strategist in Agent Development to develop and launch AI agents and advise enterprise customers.

Задачи: — Генерация визуального контента: создание качественных и фотореалистичных изображений, иллюстраций и графики в нейросетях (Midjourney, Stable Diffusion, Leonardo AI или аналогичных). — Создание и анимация видео: генерация коротких видеороликов, анимации продуктов и промо-материалов с помощью ИИ-инструментов (Runway, Pika, Sora, Kling или аналогичных). — Разработка презентаций и каталогов: верстка, оформление и сборка презентаций, коммерческих предложений и продуктовых каталогов в Canva (или российских аналогах) «под ключ» — от концепции до готового файла. — Работа с текстом и копирайтинг: написание, редактирование и адаптация текстов для презентаций, каталогов и постов с использованием ИИ (ChatGPT, Клауд, YandexGPT), контроль за тем, чтобы текст и визуал идеально дополняли друг друга. — Промпт-инжиниринг: составление, тестирование и оптимизация сложных текстовых запросов (промптов) для получения предсказуемого и коммерчески применимого результата от нейросетей. — Скаутинг ИИ-трендов: мониторинг рынка новых ИИ-инструментов, тестирование свежих обновлений нейросетей и их быстрое внедрение.

-Разрабатывать системы анализа здоровья: наше ключевое направление — AI, который помогает пользователю понять своё состояние и вовремя дойти до врача. -Внедрять AI-фичи в продукт и в компанию: интеграция LLM (онлайн и on-prem), интеллектуальный поиск, ассистенты для пользователей и внутренних команд.

DeepInfra is looking for a Software Engineering Intern to design, develop, and deploy AI model inference solutions at scale.

HeyGen is looking for an Applied AI Engineer Video Agent to build and evaluate AI agent features across the product stack.

CoinDesk is looking for an AI Forward Deployed Engineer to build and deploy internal AI tools, automate workflows, and measure operational impact.

Задачи: — На вход поступает детский рисунок → система обрабатывает его → на выходе получаем фотореалистичное изображение, сохраняя композицию, основные объекты и идею исходного рисунка. Нужно уметь: — собирать сложные workflow в ComfyUI; — работать с моделями, LoRA, ControlNet, IP-Adapter и другими инструментами; — подбирать и тестировать модели под конкретную задачу; — доводить workflow до стабильной автоматической работы. Нам нужен не просто красивый разовый результат, а стабильный рабочий pipeline для интерактивной инсталляции.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM   This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Sales Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.     ABOUT THE ROLE   You'll work on some of the hardest problems in applied AI alongside customers. This is not demos or research, but helping teams build systems they rely on in production. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Run technical demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up - Strong Python, JavaScript and systems fundamentals - Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations - Can explain technical tradeoffs clearly and build trust with developer audiences - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about operating AI agents in production, not just building demos NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $185,000–$315,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: New York, NY Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.   ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world.   WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement   WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production   NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: San Francisco, CA Workplace: OnSite ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform. ABOUT THE ROLE You'll work on some of the hardest problems in applied AI alongside customers. You will help customers adopt innovative new practices in agentic engineering, and ensure they ship reliable agents into production, quickly. The feedback loop is fast, the impact is visible, and your work directly shapes how AI agents are built in the real world. WHAT YOU’LL DO - Co-architect and co-build production AI agents with customer engineering teams and customers - Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations - Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows - Advise customers post-sale on architecture, best practices, and roadmap-level decisions - Build and run tailored demos, trainings, and workshops for developer audiences - Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers - Interface with LangChain's engineering, product and design (EPD) team to share field perspectives and guide product direction based on customer priorities - Occasionally contribute code upstream when it meaningfully improves customer outcomes - This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement WHAT YOU’LL BRING - 1-3 years of experience in software engineering, customer engineering, solutions engineering, founding engineering, or a similarly technical role, ideally at a startup or high-growth company - Strong Python, JavaScript and systems fundamentals - Hands-on experience building and deploying agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling - Strong technical communication skills and builder credibility; Can explain technical tradeoffs clearly, translate complex AI concepts into actionable insights, and build trust with technical customers and engineering teams - Excited to work directly with customers during POCs, architecture reviews, and technical evaluations - Take responsibility for outcomes, not just recommendations - Have a bias toward action and enjoy figuring things out as you go - Are excited about shipping AI agents in production NICE TO HAVE’S: - You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks - Worked with LLM evaluation, observability, or guardrails - Have experience with cloud environments (AWS, GCP, Azure), containers, and Kubernetes concepts - Have shipped and operated production software and are comfortable owning systems under real-world constraints COMPENSATION Annual OTE range: $160,000-185,000 USD Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Location: Baku Workplace: onsite ABOUT US Xsolla is a global commerce company with robust tools and services to help developers solve the inherent challenges of the video game industry. From indie to AAA, companies partner with Xsolla to help them fund, distribute, market, and monetize their games. Grounded in the belief in the future of video games, Xsolla is resolute in the mission to bring opportunities together, and continually make new resources available to creators. Headquartered and incorporated in Los Angeles, California, Xsolla operates as the merchant of record and has helped over 1,500+ game developers to reach more players and grow their businesses around the world. With more paths to profits and ways to win, developers have all the things needed to enjoy the game. For more information, visit xsolla.com. Why This Role Exists Xsolla is going all-in on becoming an AI-first company, and we're not waiting for a slow rollout to get there. We're offering AI Engineer Internships in regions across the globe to help drive that shift directly, not by sitting in the back office, but by building. You'll work on two things: Internal AI initiatives – helping unlock AI tooling and integrations across Xsolla faster than our existing teams can alone. Proof-of-concept builds on our own APIs – showing our product and engineering teams what's possible when you build with AI as a core part of your workflow, not an afterthought. This isn't a shadow-and-observe internship. You'll ship code that goes to customers – internal teams or external players and game developers – working closely with senior engineers and fellow interns across our global regions. Who You'll Work With You won't be isolated on an intern-only project island. You'll work closely with senior engineers who are actively rebuilding how we write software, and you'll be part of a global cohort of interns building in parallel across our regions. That combination is the point: senior engineers give you a bar for what production-grade, customer-facing code looks like, and your fellow interns give you a peer group to trade ideas, code, and AI workflows every week. What You'll Do Partner and collaborate with senior engineers to identify where AI tooling and integrations can remove friction, and build the fix. Build applications and integrations on top of Xsolla's APIs and SDKs that show internal teams how to move faster using AI-assisted development. Ship work that matters. What you build is expected to reach real users – whether that's an internal tool an engineering team adopts or a customer-facing integration – not a throwaway exercise that gets shelved after your internship ends. Use agentic coding tools (Claude Code, Cursor, or similar) as your default way of working – not a novelty you reach for occasionally. Share what you build. We run weekly 30-second lightning-talk demos where everyone shows how they used AI to solve something that week – you'll be expected to bring something real. Work with minimal process. You'll get context, a problem, and a mentor – the rest is on you to figure out and build. Learn from and collaborate with both directions: senior engineers who'll mentor you on production-grade practices, and fellow interns across markets you'll trade ideas and code with at the weekly demos. What We're Looking For You build things because you want to, and that you already use AI to do it faster. Genuine passion for building. You have side projects, hackathon entries, open-source contributions, or something you shipped just because you were curious. You didn't need an assignment to make it happen. Real AI fluency. You've actually used tools like Claude Code, Cursor, Copilot, or similar agentic coding tools to build something – not just asked ChatGPT to explain a concept. You should be able to explain how you used AI to get there and how you confirmed it actually worked – not someone who fires off a prompt and hopes for the best. Bias toward action. Given an ambiguous problem, you start building before you ask for a spec. Comfort with developing modern full-stack solutions – we care more about how fast you learn than what you already know cold. Open to current graduate students and recent graduates of a Computer Science, Software Engineering, or related program . How to Apply Please include: A link to a GitHub profile, deployed project, or anything else you've built – the more recent and self-directed, the better. A short answer (2-3 sentences, or a 2-minute video/Loom if you'd rather show than tell) to: “What's something hard you built recently, and why did you build it?” We're not grading for correctness or polish. We're looking for whether you have a real answer, and whether it's clear you actually did the work yourself (with AI as your tool, not your ghostwriter). Equal Employment Opportunity Statement: Xsolla is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity, or any other characteristic protected by law. We consider qualified applicants with criminal histories in accordance with the Fair Chance Act.   Criminal History Consideration: For the AI-First Engineering Intern, we will conduct a background check that may include the following: Criminal history check Employment verification Education verification   Relevance to Job Responsibilities: The background check is relevant to this position because of the following role responsibilities: Accessing confidential company data Ensuring compliance with regulatory requirements     Rights Under the Fair Chance Act: Applicants are encouraged to inquire about their rights under the Fair Chance Act. If you have questions regarding our hiring practices, please contact careers@xsolla.com.

Задачи: — Дизайн и построение LLM пайплайнов, AI агентов и RAG-систем с функциями вызова инструментов и структурированным выводом (JSON schema) — Разработка production-grade Python сервисов с использованием Django, Celery, Redis — Валидация продуктовых гипотез на основе реальных данных и аналитики — Измерение и оптимизация качества, производительности и стоимости LLM — Тесное сотрудничество с продакт-менеджерами и инженерами для превращения идей в масштабируемые решения Требования: — Опыт создания production LLM приложений — Практические знания RAG, embeddings, векторного поиска, prompt engineering и оценки LLM — Опыт работы с LangGraph, LangChain или аналогичными фреймворками — Сильный опыт Python backend (Django, PostgreSQL, асинхронное программирование) — Навыки работы с SQL и Pandas, ориентированность на данные — Владение английским языком на уровне B2-C1, русским на уровне C1 — Локация: любой город, кроме России и Беларуси Будет плюсом: — Опыт работы с векторными базами данных (Qdrant, pgvector и др.) — Опыт дообучения, классификации текста или работы с embedding моделями — Опыт с Kubernetes, gRPC или Go Условия: — Удалённая работа — Гибкий график — Профессиональное развитие Компания Mad Devs занимается решением сложных задач и созданием инновационных решений в области AI, проекты охватывают Европу, США и Юго-Восточную Азию. Вакансия направлена на революцию в юридической индустрии с помощью AI.

Хотим внедрить ИИ в маркетинг клиента. Агент для скоринга и сквозной аналитики — Meta, Google, TikTok, сайт и CRM для оценки качества рекламы.

Описание вакансии Чем предстоит заниматься Автоматизировать расчёт выплат с учётом разных форматов оформления, валют и условий оплаты, предусмотрев необходимые проверки. Улучшать обработку вопросов, связанных с выплатами: помогать HR и финансовой команде быстрее находить нужную информацию и отвечать сотрудникам.

Location: San Francisco, CA • New York, NY Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us! The AI Research team at Figma is working on the cutting edge of AI and Design. We work on optimizing agentic systems for design quality and end user experience. We build robust evaluators for Design and post-train models. We are a very collaborative, close-knit and impact-focused team of researchers and research engineers working on some of the most challenging technical problems at the intersection of AI and creativity. We are seeking PhD interns with expertise in machine learning and artificial intelligence to develop innovative AI solutions for design and creative products. Through both fundamental and applied research, your work will contribute to new AI-driven features in Figma products. This internship can take place in Winter 2027 or Summer 2027 in San Francisco or New York. What you’ll do at Figma: Drive fundamental and applied research in Generative AI with Figma product use cases in mind Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current AI models as well as enable the launch of entirely new AI-powered product features Explore the boundaries of what is possible with the current technology set and experiment with novel ideas Depending on your project, you may have the opportunity to publish your research in leading AI/ML conferences We'd love to hear from you if you have: Are a 4th or 5th year senior Ph.D student in AI, Machine Learning, Computer Vision, Natural Language Processing, Human Computer Interaction or a related field Proven expertise in AI through publications on recent advancements in AI, such as Large Language Models or Agentic systems Track record in applying machine learning techniques to projects in academia or industry Experience in Python and machine learning frameworks (such as PyTorch, TensorFlow) Experience solving sophisticated problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward While it’s not required, it’s an added plus if you also have: Related industry experience via a past internship or full-time role Experience communicating your solutions effectively to different audiences Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, Claude) to write, debug, and optimize code At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. Pay Transparency Disclosure This internship role is based in either Figma’s San Francisco or New York hub offices, and has the hourly base pay rate stated below.  Figma also offers interns a housing stipend and travel reimbursement. Figma’s compensation and benefits are subject to change and may be modified in the future. Internship $74 — $74 USD At Figma we celebrate and support our differences. We know employing a team rich in diverse thoughts, experiences, and opinions allows our employees, our product and our community to flourish. Figma is an equal opportunity workplace - we are dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity/expression, veteran status , or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. We will work to ensure individuals with disabilities are provided reasonable accommodation to apply for a role, participate in the interview process, perform essential job functions, and receive other benefits and privileges of employment. If you require accommodation, please reach out to accommodations-ext@figma.com . These modifications enable an individual with a disability to have an equal opportunity not only to get a job, but successfully perform their job tasks to the same extent as people without disabilities. Examples of accommodations include but are not limited to: Holding interviews in an accessible location Enabling closed captioning on video conferencing Ensuring all written communication be compatible with screen readers Changing the mode or format of interviews To ensure the integrity of our hiring process and facilitate a more personal connection, we require all candidates keep their cameras on during video interviews. Additionally, if hired you will be required to attend in person onboarding. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Figma's Candidate Privacy Notice . Application limits: To help candidates focus on the opportunities most relevant to their skills and experience, Figma limits the number and frequency of applications. These limits apply to all roles: Candidates may submit up to 5 applications during any rolling 30-day period. Candidates may not reapply to the same role while an application is active or within 90 days of receiving a rejection. Once the applicable days has passed, candidates are welcome to apply again.

Looking for an engineer who has hands-on experience building AI agents that actually execute workflows, not just chat interfaces. You’ll work on agents that connect to APIs and internal systems, use tools, retrieve context, make decisions across multiple steps, and recover when something fails.