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

FAIR (Meta) is the artificial intelligence research division of Meta. On-site position in Paris, France.

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: GTM Engineering builds the AI agents, systems, and automation that power how our go-to-market teams work. We partner across Sales, Marketing, Customer Success, Support, and other GTM functions to identify high-leverage problems and build solutions that improve speed, quality, and scale. Our work spans four core areas: - Identify — find high-leverage GTM workflows where AI can meaningfully improve how we operate - Build — design, build, and deploy production AI agents and automated workflows across GTM - Enable — drive adoption through thoughtful rollouts, playbooks, best practices, and ongoing enablement - Evangelize — share what we build and learn externally through content, demos, talks, and open source examples ABOUT THE ROLE: You'll own the health, cost, performance, and business impact of the GTM Agent System, and build the feedback loops that keep it improving. Because we build the platform we run on, you'll also operate the agent on LangSmith the way we tell customers to, and turn that practice into the reference story enterprises keep asking us for. You'll work across Python 3.11, FastAPI, LangGraph, DeepAgents, LangSmith, Supabase Postgres, BigQuery, Anthropic and OpenAI models, and Slack and Next.js surfaces. WHAT YOU'LL DO: - Monitor production health across every graph, catching errors, slow runs, expensive runs, and silent failures before reps report them - Triage incoming issues from Slack, tickets, and rep reports, fixing small things directly and routing the rest to the right owner - Run the weekly eval suite, investigate failures, and turn real production bugs into permanent regression tests - Track cost and latency by model, graph, use case, and role, and recommend concrete changes to model choice, reasoning effort, and caching - Track usage and adoption per rep and per feature, and own the weekly health report the team runs on - Build the business metrics that show leadership what the agent is worth, from reply rates and meetings booked to hours reclaimed and ROI - Build our own monitoring and alerting on LangSmith, and write the “how we run our own agent” story for customers WHAT YOU'LL BRING: - Strong production Python and SQL, comfortable working in traces, logs, and warehouse tables - Real experience running LLM applications, including tracing, evals, and prompt and cache mechanics - SRE or production operations instincts: percentiles, SLOs, and separating noise from real pattern - Healthy skepticism about metrics; you check what a number actually counts before you publish it - Clear writing skills, and interest in publishing what you learn - High agency; you notice what's missing and take initiative to build it NICE TO HAVES: - LangGraph or LangSmith experience - Experience building an eval suite from scratch - BigQuery or dbt - Prior DevRel-adjacent writing - Empathy for sales and go-to-market users Salary: $165,000 - $220,000 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.

Задачи: - Внедрение обученных моделей в закрытый контур экосистемы компании (на частных серверах) с обеспечением автономной работы и защиты от внешних воздействий - Адаптация и оптимизация AI-алгоритмов для эксплуатации на защищённых мобильных устройствах с учётом ограниченных вычислительных ресурсов и минимизации энергопотребления Требования: - Знание архитектур нейросетей (Transformer, CNN, RNN, GAN, Diffusion) - Владение методами обучения моделей с нуля и дообучения (fine-tune) существующих решений - Опыт работы с фреймворками PyTorch, TensorFlow, JAX - Навыки написания кода для инференса и развёртывания моделей в продакшн-среде - Понимание принципов оптимизации: градиентный спуск, функции потерь, регуляризация - Уверенное владение языками программирования Python и C++ - Способность реализовать с нуля отдельные компоненты модели, например, механизм внимания или отдельный слой - Глубокое понимание внутренней логики работы моделей

Задачи: — Создавать видео и изображения с помощью Seedance, Kling, Sora, Runway, Pika, Midjourney и других AI-инструментов; — Придумывать визуальные идеи для роликов; — Писать промпты и работать с референсами; — Монтировать видео для TikTok, Reels и YouTube Shorts. Требования: — Опыт работы с AI-инструментами для генерации видео и изображений; — Уверенное владение Premiere Pro; — Знание After Effects и Photoshop; — Понимание современных трендов и визуального стиля соцсетей; — Умение быстро собирать ролики и работать с правками; — Внимательность к деталям и соблюдение сроков. Условия: — График 5/2, офис в Астане (левый берег); — Работа в молодой команде, связанной с AI, видео и соцсетями; — Минимум бюрократии и быстрый запуск идей; — Свобода в креативе и возможность предлагать свои форматы; — Доступ к новым AI-инструментам и работа с реальными проектами.

Задачи: — Создавать видео и изображения с помощью Seedance, Kling, Sora, Runway, Pika, Midjourney и других AI-инструментов; — Придумывать визуальные идеи для роликов; — Писать промпты и работать с референсами; — Монтировать видео для TikTok, Reels и YouTube Shorts. Требования: — Опыт работы с AI-инструментами для генерации видео и изображений; — Уверенное владение Premiere Pro; — Знание After Effects и Photoshop; — Понимание современных трендов и визуального стиля соцсетей; — Умение быстро собирать ролик и работать с правками; — Внимательность к деталям и соблюдение сроков. Условия: — График 5/2, работа в офисе; — Минимум бюрократии и быстрый запуск идей; — Свобода в креативе и возможность предлагать свои форматы; — Доступ к новым AI-инструментам и работа с реальными проектами.

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE As an AI Solutions Strategist, you will sit at the intersection of customers, AI delivery, and Ramp’s core product teams. You will partner with enterprise/strategic customers to deeply understand their finance workflows—especially corporate finance and controllership priorities like close, controls, and spend governance—identify high-impact opportunities for AI and automation, and translate those needs into clear problem statements, solution designs, and actionable feedback for Ramp’s Product, Engineering, and Go-to-Market teams. This role is for someone who can listen carefully, structure ambiguity, and turn on-the-ground learnings into scalable solutions. This role required high proactivity and bias to action.   WHAT YOU'LL DO - Discover and diagnose customer needs. Run stakeholder interviews and workflow deep dives with Finance, Procurement, AP, and IT teams. Map end-to-end processes and identify the underlying drivers behind pain points — risk, cost, cycle time, compliance, exception volume, and operational complexity. - Translate needs into solution requirements. Turn qualitative input into crisp artifacts: problem statements, success metrics, constraints, acceptance criteria, and deployment plans. Balance speed, safety, and scalability across MVPs, iterations, and broader rollouts. - Partner with technical teams to implement AI workflows. Work closely with Ramp engineers and AI builders to design and ship solutions that meet real customer workflows. Specify data inputs, integrations, governance needs, policy rules, auditability requirements, and edge cases. - Drive feedback loops into Ramp's product. Synthesize learnings across customers into reusable patterns and product opportunities. Write high-signal briefs for Product and Engineering that explain what customers need, why it matters, and what should be built next. - Communicate impact and guide executives. Present status, outcomes, and recommendations to customer operators, executives, and internal stakeholders. Quantify impact through time saved, error reduction, improved compliance, faster close, and other business outcomes.   WHAT YOU NEED - 4+ years of relevant experience - Strong customer empathy and the ability to earn trust quickly with senior stakeholders. - Excellent problem framing: you can turn messy workflows into clear systems and priorities. - Comfort operating in ambiguity and iterating quickly while keeping quality high. - Ability to communicate clearly in writing (briefs, requirements, postmortems) and verbally (workshops, exec readouts). - A builder mindset: you like shipping, learning, and improving the system. - Experience in solutions, implementation, product strategy, consulting, or technical program management. - Strong grounding in corporate finance / controllership workflows, including accounting close, spend governance/controls, budgeting, procurement, and AP operations. - Experience translating finance requirements into system design and configuration (e.g., ERP/accounting, procurement, expense management, payments), including integrations, data mapping, and controls. - Ability to partner with finance system owners/admins to drive change management, testing (UAT), and successful rollouts. - Familiarity with finance operations workflows (AP, procurement, expenses, cards, accounting close). - Exposure to AI-enabled products, automation, or applied ML (you do not need to be an ML engineer). - Basic comfort with data concepts and systems integration (APIs, ETL, SQL, spreadsheets, data quality).   WORKING STYLE We collaborate best when we’re close to the work and close to each other. This role is hybrid in New York, with time in-office to partner tightly with product and engineering teams. Importantly, this role required spending time with customers to understand real workflows, so travel and flexibility are critical to success. BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: United States; New Jersey; Boston; Canada; New York; Washington, DC; Ottawa; Toronto; Montreal Workplace: Remote WHO ARE WE? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! ABOUT NORTH: North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. We’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one. Note: between 20 - 40% travel anticipated. IN THIS ROLE, YOU WILL: - Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualization through production - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution - Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization - Travel up to 20–40% to work on-site with customers and partners YOU MAY BE A GOOD FIT IF: - You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code - You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute - You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks - You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency - You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs - You have experience owning the full scope of a use case end-to-end - You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting IT'S A BONUS IF YOU HAVE: - Experience setting architectural standards for AI and agentic systems across distributed teams - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms) - Experience with enterprise security, compliance, or auditability requirements for AI systems 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.

Location: Ottawa; Canada; Vancouver; Toronto 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! ABOUT NORTH: North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? Cohere’s team partners with Canadian public sector organisations to unlock transformative value through secure, ethical deployment of Generative AI (GenAI) solutions. We work collaboratively to address complex societal challenges while maintaining the highest standards of data security and compliance. You will work directly with public sector customers to quickly understand their greatest problems and design and implement solutions using Cohere's stack. This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors. We are seeking engineers with diverse skill sets, including backend, infrastructure, agent development, and deployments, who deeply care about customers and want to work at the cutting edge of Agentic AI. Location: Ottawa (proximity to government customers), 20-40% travel anticipated. Security Clearance: Eligibility for Active Top Secret clearance is needed for this position, candidates eligible and willing to obtain clearance will also be considered. More information about Canadian Security Clearance can be found here https://www.canada.ca/en/public-services-procurement/services/industrial-security/security-requirements-contracting/personnel-security-screening/processes/security-clearance-request.html. In this role, you will: - Build and ship features for North, our AI workspace platform - Develop autonomous agents that talk to sensitive enterprise data - Experiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectations - Work across the entire product lifecycle from conceptualization through production - Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout You may be a good fit if: - You have experience with and enjoy working directly with customers - You have shipped (lots of) Python in production - You have built and deployed highly performant client-side or server-side RAG/agentic applications - You have strong coding abilities and are comfortable working across the stack. You’re able to read and understand, and even fix issues outside of the main code base - You excel in fast-paced environments and can execute while priorities and objectives are a moving target 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.

Location: North America, EU, UK AI Security Researcher / Research Engineer Remote or hybrid - London preferred but North America, EU, UK accepted About Brave: Brave is on a mission to protect the human right to privacy online. We’ve built a free web browser that blocks creepy ads and trackers by default, a private search engine with a truly independent index, private AI assistant, latest privacy and security features, and a private ad network (opt-in!) that directly rewards you for your attention. Already over 120 million people regularly use Brave for a faster, more private web. Millions more switch every month. The internet is a sea of ads, hackers, and echo chambers. Big Tech makes huge profits off our data, and tells us what’s true and what’s not. Brave is fighting back. Join us! Summary We are looking for a researcher/research engineer to help mitigate the security risks that come with building AI systems-especially LLM-powered web agents and chatbots. In this role, you'll design and implement secure-by-design architectures, audit our LLM-powered web agent (https://brave.com/blog/ai-browsing/) and chatbot, and help set Brave's direction on how we identify, measure, and reduce security risk across AI products. Responsibilities Design and execute adversarial evaluations to uncover failure modes in LLM-powered web agents and chatbots (e.g., prompt injection, tool abuse, data exfiltration) Analyze model behavior (including internal thoughts) to understand and forecast security risks in frontier models Develop and prototype security-focused training and fine-tuning techniques Augment web agents with security principles including information flow control, privilege control and contextual security Partner with engineers and (privacy, ML, and Cryptographic) researchers to translate findings into product changes, tests, and measurable security improvements Help define a forward-looking security strategy and policy for building and responsibly releasing web agents—advocating for user protection You may be a good fit if you have Demonstrated experience working on Secure AI (prompt injection attacks and security guardrails) Strong publication record in AI security, ML security, or closely related areas A track record of shipping products and features inside a fast-moving environment Strong coding skills in Python and familiarity with ML frameworks like PyTorch or JAX Experience training, fine-tuning, and evaluating large language models Deep familiarity with large language models and web agents, how they work, and how they are trained Experience applying security principles (e.g., information flow control, access control/least privilege) Demonstrated success in bringing clarity and ownership to ambiguous technical problems A Ph.D. in computer science is highly preferred, but we may consider some exceptions with industry experience Skills That Will Set You Apart from the Competition Knowledge of AI Systems (pipelines, security evaluation, etc.) Open source projects on security/privacy Experience with confidential computing and ZKP/SMPC protocols Ph.D. in computer science from a top-tier school A strong publication record in premier systems, performance, or ML Work experience in industry is desirable Working at Brave - What we offer Ability to work at an exciting and well-funded international startup headquartered in San Francisco Cutting-edge technology, allowing you to work with state-of-the-art tools and software solutions Competitive compensation and plenty of room for personal growth Great international exposure and team atmosphere We are looking to hire in London but would consider an exceptional candidate in the rest of Europe. NO AGENCIES or RECRUITERS PLEASE - Unfortunately, we cannot work with third parties on these searches.

Задачи: — Проектирование и разработка микросервисной архитектуры на Java 17+ с использованием Spring Boot (MVC, Data JPA, Security) — Построение пайплайнов Retrieval-Augmented Generation (RAG): от парсинга сырых данных до индексации эмбеддингов — Разработка и поддержка векторных баз данных Qdrant: проектирование схем шардирования, настройка гибридного поиска (BM25 + Dense Vectors) и оптимизация запросов — Создание мультиагентных систем на базе LangChain/LangGraph для автоматизации бизнес-процессов — Глубокий промт-инжиниринг: написание промптов под разные сценарии одного агента, техники Few-shot, Chain-of-Thought, структурированный вывод (JSON mode) — Отладка семантики моделей: снижение энтропии ответов, управление вариативностью через параметры инференса, механизмы self-healing при деградации внешних провайдеров LLM — Оптимизация производительности PostgreSQL: тюнинг сложных SQL-запросов, работа с индексами (B-tree, GIN/GIST, триграммы), проектирование транзакционной изоляции — Вынос вычислений в контейнерную среду: Docker, Kubernetes (Helm), построение отказоустойчивых CI/CD-конвейеров в GitLab CI/Jenkins Требования: — Уверенное владение Java 17+, понимание многопоточности (CompletableFuture, виртуальные потоки Project Loom — будет плюсом) — Экспертный уровень владения стеком Spring: жизненный цикл бинов, аспектно-ориентированное программирование, тонкая настройка пулов соединений БД и параметров безопасности — Опыт проектирования реляционных моделей в PostgreSQL, умение читать EXPLAIN ANALYZE, эффективные миграции (Liquibase/Flyway) — Практический опыт работы с векторными СУБД (Qdrant) или Weaviate/Pinecone/Milvus, понимание метрик близости (Cosine Similarity, Dot Product, Euclidean Distance) — Опыт разработки с библиотеками LangChain и/или LangGraph, построение графов состояний, интеграция внешних инструментов (tool calling) — Навык написания эффективных промптов (Prompt Engineering) и управления поведением LLM без изменения весов модели — Опыт работы с Docker и Kubernetes (манифесты, Helm-чарты), знание Linux shell на уровне уверенного пользователя — Настроенные процессы CI/CD (GitLab CI или Jenkins): сборка Maven/Gradle, покрытие тестами (JUnit 5, Testcontainers), статический анализ кода

Location: San Francisco Bay Area, California; New York City Metropolitan Area Workplace: remote About the role: Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and are obsessed with reimagining how they operate and compete. Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture. We embed engineers and leaders inside client operations as Forward Deployed Engineers (FDE) and Forward Deployed Executives (FDX) — people who learn the work, ship the system, and own the outcome. Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Bluprints. You will do the customer’s job before you automate it. Most AI engagements fail the same way: someone gathers requirements, someone writes a PRD, and a team ships a workflow nobody uses. We think the requirements-gathering step is the bug. So we remove it. A Forward Deployed AI Engineer at Provectus spends the first weeks of an engagement in the operator’s seat — as the underwriter, the analyst, the RCM specialist, the claims clinician, whoever actually does the work we’ve been asked to change. You do the job. You learn the constraints from the inside, the ones nobody writes down. Then you sit at a table with that operator and a Forward Deployed Executive and rebuild the function from first principles — and you are the one who builds it. Three things define how you work: Embedded, not engaged . You are part of the customer’s team and inside their process — not a vendor running a project alongside it. Real tasks, not scope . You are not fenced into a siloed deliverable. You go where the operating problem is. Autonomous . Embedded is not staff-augmented. You own the method; nobody hands you a ticket. You won’t start from zero. Provectus builds industry blueprints — working systems that have already shipped for a customer in your industry. Your engagement starts from that baseline, and what you learn in the field goes back into it. That loop is the difference between an outcome and an invoice. You’ll be measured on whether the Business Unit’s number moved — not on hours, not on scope delivered. This is a role for engineers who have led before — as a founder, a CTO, a staff engineer — and who want to stay in the code while owning the outcome. On most days you’ll be the most senior technical person in the room, and you’ll still be the one shipping. Requirements: 8+ years building software , a substantial share of it writing production code you were accountable for. You are hands-on today and intend to stay that way. You will take the operator’s seat. You are genuinely willing to spend weeks doing someone else’s job — claims processing, underwriting, revenue-cycle work — before you write a line of code. Engineers who need to stay in the IDE should not apply. You learn domains fast. Demonstrated ability to become conversant in an unfamiliar business function quickly enough to argue with the people who do it for a living. Shipped GenAI/LLM systems to production — not demos, not notebooks. You’ve handled the parts that get hard after the prototype works. You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured and why. Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack. Cloud-native delivery on AWS (GCP/Azure a plus): containers, Kubernetes/ECS, IaC, CI/CD, and the operational reality of a system someone else inherits. Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO without losing either room. Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job. Solid AI/ML foundations — you understand what the models do well enough to reason about failure modes, not just call the API. Strong hands-on prodcution experience with Claude Code/Cowork. Fluent English, written and spoken. Nice to have: Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution. Real depth in one of our blueprint industries: financial services, insurance, healthcare, asset management . Consulting, professional services, or other embedded customer-facing delivery. Data platform depth: data lakes, warehouses, streaming and real-time analytics, data mesh and data contracts, governance and data quality. MLOps and classical ML: PyTorch, SageMaker, MLflow. Fine-tuning, distillation, or inference/serving optimization. Graph databases (Neo4j, AWS Neptune). IaC depth: AWS CDK, CloudFormation, Terraform. Open-source contributions or public writing on applied AI. What you’ll do: Take the seat Do the operator’s job for two to four weeks at the start of an engagement. Learn the function from inside, not from a requirements doc. Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow — in weeks, not quarters. Sit with the operator and the Forward Deployed Executive and redesign the function from first principles. Discovery, user research, and PRD-writing collapse into one team that re-imagines its own job. You are all three roles. Build Ship production GenAI systems into the customer’s environment — LLM applications, agentic workflows, retrieval and structured-extraction pipelines, and the services around them. Running software, not recommendations. Build the evaluation harness before you build the feature. When the engagement is bound to a business KPI, “it looked good in testing” is not an answer. Define what working means, instrument it, and let the evals drive the design. Write production code across the stack — backend services, data pipelines, and the AI layer. Python and TypeScript are our centre of gravity; we choose tools to fit the customer, not the résumé. Take systems to production on AWS (GCP/Azure where the customer requires it): containerized, observable, and maintainable after we leave. Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from. Own the outcome Work in a pair with a Forward Deployed Executive who carries the Business Unit’s KPIs. Your work is measured against the same number. Drive adoption. A system the BU routes around has not shipped. Change management is part of the engineering job here, not a phase after it. Be credible with the customer’s engineers, their operators, and their executives — and be willing to disagree with all three. Shape what we commit to before we commit to it. You’ll have the standing to do it, because you’re the one who will build it. What We Offer: Frontier delivery work across Cowork Activation, Agentic SDLC, and Blueprint Activations in Financial Services and Healthcare The chance to shape how leading enterprises adopt AI, from strategy through first deployment A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers A growing AI delivery practice where you help build the tooling and frameworks, not just use them Remote-friendly culture High-impact role with direct visibility to leadership. Strong earning potential with performance-based bonuses. Opportunity to work with cutting-edge AI and cloud solutions. B2B contract model or full-time model. Unlimited Vacation policy. Generous health, vision, and dental insurance. 401(K) matching plan. OTE range: up to $250k. The salary range is determined through interviews and a review of the education, experience, knowledge, skills, abilities of the applicant, and alignment with market data. How we hire: Intro conversation — the role, your background, what you want to be doing. Two live engineering sessions. Real problems, your own editor. You may use an LLM assistant (ChatGPT, Claude) — how you work now includes these tools. Autocomplete/agentic coding tools are off for these sessions. The redesign session. We hand you an unfamiliar business function and the constraints of the person who performs it. You have to understand the job well enough to rebuild it — then say what you’d build and how you’d know it worked. No LLMs for this one. Team and practice conversation.

Location: New York, NY (HQ) Workplace: Hybrid ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $275B in annualized spend flows in and out of 85,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 7.5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE Ramp is building a new AI business, and you’ll be one of its first technical sellers. Your job is to turn technically complex AI products into closed revenue. You’ll sell a growing portfolio spanning AI-powered applications and agents for finance teams, as well as infrastructure that helps companies deploy and manage AI with greater control, security, and cost efficiency. This is a product-focused, quota-carrying technical sales role. You’ll help customers evaluate and purchase Ramp’s AI products, translating complex capabilities into clear business value and guiding opportunities from discovery through close. This is a high-velocity commercial role, not a traditional pre-sales position where success ends with a great demo. You’ll be accountable for turning technical evaluations into commercial wins from start to finish. You’ll lead discovery, shape deal strategy, build executive-level business cases, deliver tailored demonstrations, navigate technical and commercial objections, and create urgency around a clear path to purchase. You’ll move comfortably between technical and executive conversations. In one meeting, you may discuss model routing, APIs, integrations, data governance, and security with Engineering and IT teams. In the next, you may help Finance and executive leaders understand the ROI, total cost of ownership, and operational impact of adopting Ramp’s AI products. You’ll join at a formative moment for Ramp’s AI business. As one of the first dedicated sellers for these products, you’ll help identify the strongest use cases, refine how we position and sell the portfolio, influence the customer experience, and build the playbook the broader team will eventually scale. You’ll own the full customer lifecycle from discovery and evaluation through close, implementation, and adoption, helping customers translate their purchase into a successful deployment. This role combines Ramp’s resources and customer reach with the ownership, speed, and ambiguity of an early-stage team. WHAT YOU’LL DO - Carry a revenue quota and own the progression of AI product opportunities from initial discovery through purchase, ensuring business value is clear, technical requirements are validated, and obstacles to a decision are resolved. - Lead discovery with business and technical buyers to understand their goals, workflows, challenges, decision criteria, existing systems, and AI strategy. - Translate Ramp’s AI applications and infrastructure into compelling solution narratives tied to measurable business outcomes. - Build ROI and total cost of ownership analyses that quantify the value of Ramp’s AI products and create executive-level justification for investment. - Help customers identify high-value use cases, set realistic expectations, and establish a credible path from evaluation to production. - Deliver tailored demonstrations, technical workshops, and proofs of concept with clear success criteria that establish value and build confidence in a purchase decision. - Build relationships with champions and decision-makers across Engineering, IT, Security, Finance, Operations, Procurement, and executive leadership. - Navigate questions related to APIs, integrations, model capabilities and limitations, data flows, architecture, privacy, security, governance, implementation, and tradeoffs among quality, cost, latency, and control. - Apply strong commercial judgment to qualify opportunities, create urgency, address objections, identify risk, and keep customers moving toward a decision. - Lead customers through implementation after purchase, including deployment planning, stakeholder alignment, workflow design, technical coordination, enablement, and adoption. - Partner with Account Executives and collaborate with Product, Engineering, Security, Marketing, and post-sales teams to remove deployment blockers and deliver a strong customer experience from evaluation through production. - Bring structured customer and market feedback to internal teams to improve the products, positioning, sales execution, and customer experience. - Turn early customer conversations into repeatable messaging, demonstrations, qualification criteria, value stories, and sales plays as we build this go-to-market motion from the ground up. WHAT YOU’LL BRING - 5+ years of experience in Solutions Engineering, Solutions Consulting, technical sales, Solutions Architecture, enterprise software sales, or a related customer-facing role. - Direct quota-carrying or deal-closing ownership of the pre-sale cycle—not only experience delivering demonstrations or supporting post-sale implementation. - A track record of independently influencing and winning complex B2B sales opportunities with clear revenue accountability. - Strong discovery and value-selling skills, with the ability to connect technical capabilities to measurable business outcomes. - Demonstrated ability to build executive-level business cases, including ROI and total cost of ownership analyses; this capability will be central to success in the role. - Commercial instincts and comfort taking meaningful ownership of deal strategy, momentum, and results. - Technical fluency across modern AI systems, including applications and agents, model capabilities and limitations, APIs, integrations, data flows, security, governance, and tradeoffs among quality, cost, latency, and control. - Excellent executive communication and presentation skills, including the ability to make complex concepts clear and relevant to different audiences. - The ability to explain probabilistic, rapidly evolving AI technology with credibility and precision without overpromising what the product can do. - Experience building champions and navigating multi-threaded buying groups with competing priorities. - High ownership, curiosity, sound judgment, and comfort operating in a fast-moving environment where you’ll build structure as you go rather than inherit it. - Energy for zero-to-one work and the opportunity to build a sales motion rather than simply inherit one. NICE TO HAVE - Experience selling AI infrastructure, AI applications or agents, developer tools, data platforms, security products, finance technology, or workflow automation software. - Experience helping launch a new product or develop an early go-to-market motion. - Familiarity with AI gateways, model routing, usage controls, data governance, or enterprise AI deployment. - Experience selling to developers, IT, Security, Finance, Operations, Procurement, or executive stakeholders. - Experience creating reusable sales assets, demonstrations, value frameworks, or enablement programs. BENEFITS AVAILABLE TO ALL FULL-TIME RAMP EMPLOYEES (GLOBAL) - Flexible PTO - Centralized home-office equipment ordering - Health and wellness stipend - Budget for intra-office travel - Weekly coffee stipend UNITED STATES - 100% medical, dental & vision insurance coverage for you, with partial coverage for dependents - One Medical annual membership - 401(k), including employer match on contributions made while employed by Ramp - Fertility HRA (up to $10,000 per year) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay - Pet insurance - In-office perks: lunch, snacks, drinks, and more - Relocation expense coverage to NYC or SF (if needed) CANADA - Group medical, dental, and vision coverage through Sun Life - Life, AD&D, and disability coverage - Fertility drug coverage (up to $4,000 lifetime) - Group Retirement Plan with employer match (RRSP + DPSP) - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay, with additional time available at reduced pay - Employee Assistance Program and virtual care through Lumino Health UNITED KINGDOM - Private medical insurance through Freedom Elite - Virtual GP and at-home care via eMed x Livi - Workplace pension through Penfold, with salary sacrifice option - Parental leave: up to 16 weeks (birthing + bonding) or 8 weeks (bonding only) at 100% pay with additional time available at reduced pay REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.   OTHER NOTICES Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.   Beware of recruiting scams: Ramp will only contact you through official @Ramp.com http://Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.   Ramp Applicant Privacy Notice https://ramp.com/legal/applicant-privacy-notice

Location: North America, EU, UK AI Systems Researcher / Research Engineer London (Preferred) - Hybrid, or Remote in North America, EU, UK About Brave Brave is on a mission to protect the human right to privacy online. We’ve built a free web browser that blocks creepy ads and trackers by default, a private search engine with a truly independent index, private AI assistant, latest privacy and security features, and a private ad network (opt-in!) that directly rewards you for your attention. Already over 120 million people regularly use Brave for a faster, more private web. Millions more switch every month. The internet is a sea of ads, hackers, and echo chambers. Big Tech makes huge profits off our data, and tells us what’s true and what’s not. Brave is fighting back. Join us! Summary Join us at Brave as we redefine the future of online experiences with a range of cutting-edge, top-performing products. We’re seeking an experienced AI Systems and Performance Researcher/Engineer to shape and improve our performance evaluations and optimizations across desktop and mobile. If you’re passionate about innovation, privacy, and delivering impactful AI solutions, this is your opportunity to make a difference. We need you to help with a wide range of key products, ranging from our browser ML models, novel applications, on-device AI agents, performance evaluations, and collaborating closely with privacy and security researchers to protect the users from AI risks. About you An ideal candidate will have a mix of skills that include the following: Demonstrates a high level of initiative and consistently delivers high-quality solutions Has an enquiring mind and a disciplined scientific approach to extracting facts and understanding observed behavior Is excited by the potential of realizing high-value commercial outcomes and change the way that the advertising business operates Want to be part of a high-growth startup company with global ambitions Experience with software development practices (Python, C++, JavaScript and/or Rust) Has a proven track record implementing data driven products and a broad understanding of the state of the art in systems and networks Comfortable working in an open-source setting Able to create and deploy mobile/desktop applications and systems Has a passion for helping protect users’ privacy and security A Ph.D. in computer science is highly preferred, but we may consider some exceptions with industry experience Specific Skills Background and/or previous work in AI systems research and performance evaluation. Expertise in optimizing and evaluating ML models and/or privacy & security technologies for on-device performance. Experience with modern Machine Learning (ML) frameworks (e.g., Pytorch, TensorFlow, MLX, ONNX Runtime, Core ML, TensorRT, etc.). Skills That Will Set You Apart from the Competition ML Systems (pipelines, performance evaluation, etc.) Open source projects on mobile/desktop systems optimization Experience with confidential computing and security/privacy protocols Ph.D. in computer science from a top-tier school A strong publication record in premier systems, performance, or ML Work experience in industry is desirable Working at Brave - What we offer Ability to work at an exciting and well-funded international startup headquartered in San Francisco Cutting-edge technology, allowing you to work with state-of-the-art tools and software solutions Competitive compensation and plenty of room for personal growth Great international exposure and team atmosphere We are looking to hire in London but would consider an exceptional candidate in the rest of Europe. NO AGENCIES or RECRUITERS PLEASE - Unfortunately, we cannot work with third parties on these searches.

Location: New York, NY Workplace: Hybrid We are building AI to simulate the world through merging art and science. We believe that world models are at the frontier of progress in artificial intelligence. Language models alone won’t solve the world’s hardest problems – robotics, disease, scientific discovery. Real progress requires models that experience the world and learn from their mistakes, the same way that humans do. And this kind of trial and error can be massively accelerated when done in simulation, rather than in the real world. World models offer the most clear path to general-purpose simulation, changing how stories are told, how scientific progress is made and how the next frontiers of humanity are reached. Our team consists of creative, open minded, caring and ambitious people who are determined to change the world. We aspire to continuously build impossible things and our ability to do so relies on building an incredible team. If you are driven to do the same, we'd love to hear from you. *Titles posted to our careers page are updated regularly to best advertise the role and expected seniority, but internally we have a flat titling system with two types of titles: one for individual contributors and one for people managers. ABOUT THE ROLE *Open to hiring remote across the US and London— we also have offices in NYC, San Francisco, Seattle, and London We are looking for a highly-motivated senior IC who will work with some of Runway’s biggest and most strategic partners. You will be central to our partners’ success in adopting Runway to transform the ways they create content. Success in this role will require a mix of technical fluency, strategic thinking, and hands-on execution. WHAT YOU’LL DO - Own deep, trusted C-suite level relationships with Runway's most strategic partners (from Hollywood studios to Fortune 100 enterprises) ensuring they're not just customers, but long-term partners at the frontier of AI-driven creativity and innovation - Be in the room where it happens: collaborating directly with world-class creative teams at the biggest Hollywood studios, brands, and F100 companies to co-create Emmy award-winning shows, Oscar-winning movies, Super Bowl commercials, and cultural moments that define a generation - Operate as a strategic thought partner internally: codifying the use cases we know work today while pioneering the ones that don't exist yet, and translating both into initiatives that shape Runway's product strategy and industry positioning - Get embedded within accounts to learn and understand their (content) pain points and challenges today, then propose discrete ways in which Runway can solve those challenges - Identify and prototype specific and highly targeted new markets and new opportunities for our products - Develop a deep, functional and technical understanding of our products and future roadmap - Be hands-on in quickly onboarding new partners to our platform and/or API while also supporting their long-term expansion and technical understanding of how to leverage Runway - Provide high-impact feedback to Product, Engineering, and Creative which can in turn improve the product experience for our partners - Analyze, track, and report on the performance of existing partnerships leveraging BI tools and data WHAT YOU’LL NEED - 5+ years of overall experience in customer-facing roles, engaging C-level technical audiences with complex global organizations ideally within tech, finance, or consulting - Have led complex implementations of Generative AI/traditional ML solutions and can drive measurable business outcomes - Ability to work in a fast-paced, dynamic environment and manage multiple priorities with expansive ownership and ruthlessly prioritize - A strong bias towards action and belief that no task is too small for you - Have a track record of rapidly prototyping ideas and a willingness to work iteratively with your customers to deliver the right solution that solves their problem - Possess exceptional presentation and communication skills, particularly when engaging with executives and leaders - High technical aptitude for understanding complex technologies, tools, systems, and issues - Mindset to think creatively and think beyond past checklists and playbooks - Highly resourceful with the ability to create structure and work autonomously amidst ambiguity - Nice to have but not required: experience with data tooling and BI systems (SQL, BigQuery, Retool, etc) - New York, SF, or London-based preferred Runway strives to recruit and retain exceptional talent from diverse backgrounds while ensuring pay equity for our team. Our salary ranges are based on competitive market rates for our size, stage and industry, and salary is just one part of the overall compensation package we provide. There are many factors that go into salary determinations, including relevant experience, skill level and qualifications assessed during the interview process, and maintaining internal equity with peers on the team. The range shared below is a general expectation for the function as posted, but we are also open to considering candidates who may be more or less experienced than outlined in the job description. In this case, we will communicate any updates in the expected salary range. Lastly, the provided range is the expected salary for candidates in the U.S. Outside of those regions, there may be a change in the range, which again, will be communicated to candidates. WORKING AT RUNWAY Great things come from great teams. https://www.youtube.com/watch?v=kwmj4ato2kw&ab_channel=Runway We’d love to hear from you. We’re committed to creating a space where our employees can bring their full selves to work and have equal opportunity to succeed. So regardless of race, gender identity or expression, sexual orientation, religion, origin, ability, age, veteran status, if joining this mission speaks to you, we encourage you to apply. More about Runway - Universal World Simulator https://runwayml.com/world-simulator.html - GWM-1 https://runwayml.com/research/introducing-runway-gwm-1 - Gen-4.5 https://runwayml.com/research/introducing-runway-gen-4.5 - General World Models https://runwayml.com/research/introducing-general-world-models - Robotics SDK https://runwayml.com/research/introducing-runway-gwm-1#robotics-section - Conversational Real-time Agents https://runwayml.com/research/introducing-runway-gwm-1#avatars-section - Runway Studios https://runwayml.com/studios We're excited to be recognized as a best place to work: Crain's https://www.crainsnewyork.com/awards/best-places-work-2023 | InHerSight https://www.inhersight.com/companies/best/city/new-york-city-ny | BuiltIn NYC https://builtin.com/awards/new-york-city/2024/best-places-to-work | INC https://www.inc.com/best-workplaces/2024

Location: Brazil Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. What You’ll Do Embed within client environments, working onsite with the people performing the work and the executives sponsoring it. Lead discovery sessions to understand the client’s business, systems, data, operating model, and underlying challenges. Translate ambiguous business problems into prioritized and quantified opportunity maps, supported by clear baselines and accountable client owners. Identify which opportunities are genuinely worth pursuing and advise against initiatives that do not provide sufficient business value. Build trust in the client’s data and deliver working, data-grounded prototypes within the first weeks of an engagement. Design, develop, debug, and deploy production-grade AI agents, integrations, data pipelines, and applications within client systems. Remain hands-on in the code whenever technical progress or delivery outcomes depend on it. Define evaluation frameworks, quality thresholds, regression gates, and monitoring strategies for AI and agentic systems. Monitor model and data drift and design effective human-in-the-loop controls for high-impact workflows. Scope, sequence, and coordinate delivery across engineers, architects, and specialist contributors. Make explicit trade-offs between scope, delivery speed, quality, and business value. Orchestrate Exadel Colleague to accelerate delivery and scale successful implementation patterns. Convert successful deployments into reusable reference architectures, agent templates, integration blueprints, evaluation frameworks, and delivery playbooks. Produce clear technical documentation, operational runbooks, and knowledge-transfer materials. Train client teams to independently operate, maintain, and extend delivered solutions. For Senior FDEs, independently lead executive discovery, direct pod execution, and take full accountability for engagement outcomes. For Senior FDEs, mentor other Forward Deployed Engineers and ensure reusable delivery patterns are incorporated into Exadel Colleague. What You Bring Mid-level hands-on technical experience, including client-facing capacity. For the Senior Forward Deployed Engineer level, senior-level experience, including technical delivery leadership across multidisciplinary teams or pods. A demonstrated record of delivering production software used by real users and business teams. Practical experience designing, deploying, and debugging LLM-backed or agentic systems in production. Advanced proficiency in Python, along with experience using TypeScript or JavaScript and SQL. Strong knowledge of prompt and context engineering, agent architecture, tool and function calling, and retrieval-augmented generation. Experience with Model Context Protocol servers, sub-agents, skills, and agent development frameworks such as the OpenAI Agents SDK or Claude SDKs. Experience designing evaluation harnesses, quality thresholds, regression gates, drift monitoring, and observability for non-deterministic systems. Understanding of human-in-the-loop control design and where human review should remain within automated workflows. Experience with data modeling, domain ontologies, ETL or ELT pipelines, relational databases, vector stores, and embedding pipelines. Experience building and deploying solutions on AWS, Azure, or GCP. Familiarity with Docker, Kubernetes, CI/CD, infrastructure as code, serverless architectures, and enterprise deployment patterns. Experience integrating with REST or GraphQL APIs, webhooks, event-streaming platforms, identity systems, and SSO. High agency and sound judgment when working through ambiguity, incomplete information, and evolving client requirements. Demonstrated ability to become credible and productive quickly within unfamiliar industries and business domains. A habit of clarifying the problem, identifying constraints, and explicitly stating assumptions before developing a solution. The ability to communicate effectively with both executive and technical audiences. Strong technical writing skills, with the ability to explain complex concepts clearly and precisely. Commercial judgment and the ability to connect technical decisions to measurable business value. Strong analytical and mathematical rigor when working with incomplete, inconsistent, or unstructured data. Fluent English communication skills. Willingness to travel approximately 25–50% and work onsite in client environments. Nice to have A university degree is preferred but not required. Demonstrated evidence of successfully delivered work will be valued ahead of formal qualifications. Java, C#, or C++ within legacy enterprise environments. Node.js, React, or Next.js for client-facing applications. Fine-tuning fundamentals and multi-agent orchestration. TDD or BDD practices. Large-scale data processing platforms such as Spark, Databricks, or Snowflake. PostgreSQL, MySQL, or comparable relational databases. On-premises, sovereign, or restricted-cloud deployment models. Enterprise systems such as Jira, Azure DevOps, ServiceNow, Salesforce, or SAP. GitHub or GitLab-based delivery workflows. English level Fluent Legal & Hiring Information Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more Reasonable accommodations are available to enable individuals with disabilities to perform essential functions Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs Compensation details are shared with candidates at the early stage of the recruitment process. The offer is not binding until a signed contract is in place. This position supports US-based operations; however, contracting will be executed locally in Brazil as a [PJ / CLT] engagement. Compensation is set and paid strictly in Reais (BRL). Your Benefits at Exadel Exadel benefits vary by location and contract type. Your recruiter will fill you in on the details. International projects In-office, hybrid, or remote flexibility Medical healthcare Recognition program Ongoing learning & reimbursement Well-being program Team events & local benefits Sports compensation Referral bonuses Top-tier equipment provision Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Задачи: — Проектирование, создание и внедрение AI-агентов для автоматизации и поддержки ключевых бизнес-процессов в Sales, Marketing, Customer Success, Customer Support, Risk и Finance. — Разработка архитектуры и оркестрация агентских систем, включая управление инструментами, памятью, многошаговое планирование, эскалацию с участием человека, защитные механизмы и аудит, соответствующие требованиям финтех-компании. — Создание и поддержка RAG-пайплайнов, обеспечивающих работу агентов на основе внутренней базы знаний Tipalti: документация, данные клиентов, финансовые записи, внутренние инструкции, с использованием векторных баз данных, гибридного поиска и переоценки результатов. — Определение и внедрение систем оценки агентов по таким метрикам, как выполнение задач, точность, уровень галлюцинаций, задержки и бизнес-эффект, с последующей итеративной доработкой на основе данных и отзывов заинтересованных сторон. — Взаимодействие с различными подразделениями компании для выявления кейсов использования агентов, трансформации бизнес-требований в технические задачи и доставки продуктов с измеримым ROI. Требования: — Высшее образование в области компьютерных наук, инженерии или смежных дисциплин с акцентом на искусственный интеллект. — Опыт работы не менее 3 лет в области AI/ML-инжиниринга, предпочтительно в финтехе или смежных сферах, с успешным опытом внедрения AI-агентов или агентских рабочих процессов в продакшн. — Владение Python и SQL для обработки данных, анализа и построения AI-систем. — Глубокие знания LLM и prompt engineering, включая систематическую оценку корпоративных AI-решений. — Опыт создания RAG-систем и разговорных чатботов будет преимуществом. — Опыт работы с облачными платформами, предпочтительно AWS, для деплоя и AI-Ops практик. — Аналитический склад ума, умение критически оценивать AI-решения и их влияние на бизнес. — Навыки управления проектами, способность расставлять приоритеты и балансировать краткосрочные и долгосрочные задачи для своевременной реализации результатов. Условия: — Возможность удалённой работы. — Гибридный формат работы в офисе в Тель-Авиве (2 дня дома, 3 дня в офисе) с предоставлением трансфера, парковки, снеков. — Конкурентные социальные гарантии, карьерное консультирование и поддержка разнообразия в коллективе. Компания Tipalti — платформа автоматизации финансов, работающая с более чем 5000 компаниями по всему миру, сотрудничает с ведущими финансовыми институтами и обеспечивает выплаты в 120 валютах по 200+ странам. Tipalti поддерживает инклюзивность и равные возможности для всех кандидатов.

Location: Atlanta, GA 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 The Deployed Engineering 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 The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do 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 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: $150,000–$250,000 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.