Вакансии

💎 Компания Selecty ищет Data‑инженера / разработчика витрин для разработки витрин (70–80 % задач), сопровождения на уровне 3‑й линии (20–30 %), поднятия витрин в MVP с нуля, реализации витринной разработки и интеграции с командой веба.

-Проектировать и реализовывать агентное ядро — turn-loop, оркестрацию tool-calling, управление подагентами, контекст-менеджмент: компакция и токен-бюджеты, промпт-архитектура, устойчивый роутинг моделей с graceful degradation.

– Экспертиза в архитектуре реляционных/нереляционных СУБД и брокеров сообщений: PostgreSQL, ClickHouse, Redis, MongoDB, Kafka. – Опыт администрирования крупной инфраструктуры (тысячи кластеров) БД и брокеров сообщений с SLA от 99,9%.

Location: São Paulo Workplace: Hybrid adjoe https://adjoe.io/ está redefinindo o futuro dos anúncios mobile. Impulsionados por IA avançada, dados proprietários e engenheiros de classe mundial, aperfeiçoamos a experiência de offerwall para monetizar e escalar publishers de aplicativos com soluções como Playtime e Arcade – o canal de publicidade recompensada que cresce mais rápido globalmente – gerando engajamento, retenção e receita incrementais. Ao mesmo tempo, estamos entrando na publicidade programática com o sistema de lances inteligentes da adjoe Ads. Juntos, este ecossistema conecta desenvolvedores de aplicativos a mais de 600 milhões de usuários em todo o mundo para um crescimento escalável. Apoiados por um investimento de U$ 100 milhões da Bertelsmann e operando em escritórios em Hamburgo, Boston, Cingapura, São Paulo e Tóquio, a adjoe está definindo os próximos estágios da experiência de aplicativos e anúncios. Junte-se a nós. Estamos procurando um Arquiteto de Soluções Sênior para apoiar na dimensão técnica e de produto dos relacionamentos empresariais mais críticos da adjoe. Atuando como "Líder Técnico" para nossos parceiros, você mesclará roteiros de parceiros complexos com nossa stack moderna – alimentada por Golang e SDKs Nativos – para impulsionar a excelência técnica para mais de 100 milhões de usuários diários. Seu papel será fazer a ponte entre nossa equipe de tecnologia na Alemanha e a visão do parceiro. Você colaborará com contrapartes sêniores de produtos e engenharia, atuando como um ponto de contato para todo o discurso técnico. Este é um papel de profundo empoderamento técnico: você tem acesso direto a toda a nossa infraestrutura em nuvem – desde monitoramento e registro em tempo real até nossos extensos data lakes – para manter uma visão abrangente e completa do estado do sistema. Desde a investigação de problemas arquitetônicos complexos até o apoio à implantação de novos recursos de alto impacto, você garante que nossas tecnologias evoluam em perfeita sintonia. Trabalhando como um colaborador-chave nos departamentos internos de Produto e Tecnologia, você atuará como guardião técnico e defensor de nossas maiores contas empresariais. O Que Você Fará: - Estratégia Técnica & Execução: Atuar como o consultor principal para parceiros empresariais, arquitetando o caminho técnico para o sucesso. Você desempenhará um papel fundamental na orientação da co-criação de novos produtos em parceria com nossa equipe de tecnologia sediada na Alemanha, validando e otimizando soluções técnicas diretamente com nossos principais parceiros para garantir que sejam testadas na prática, antes de atingir a produção em escala total. - Orquestrar o Roteiro Técnico Conjunto: Apoiar o ciclo de vida técnico da parceria, liderando implantações complexas de recursos e gerenciando cronogramas de integração. - Arquitetura de Causa Raiz & Mitigação Proativa: Coloque seu "chapéu de detetive" para liderar a solução de problemas de alto risco, indo além da superfície do código de aplicativos mobile para realizar análises aprofundadas de causa raiz, identificando e resolvendo proativamente bloqueadores de integração antes que impactem a receita do parceiro. - Consultoria Baseada em Dados: Aproveitar SQL e Python (ou outros) para agregar e visualizar conjuntos de dados complexos, traduzindo dados brutos em narrativas técnicas que ajudam os parceiros a atingir seus KPIs. - Voz do Cliente: Traduzir o feedback dos parceiros em requisitos técnicos precisos para equipes internas de Produto para desbloquear a escalabilidade global. - Propriedade de Contas Empresariais: Servir como o ponto de contato técnico dedicado para contas empresariais importantes, possuindo relacionamentos com partes interessadas sêniores em produto, engenharia e liderança. Você apoiará discussões técnicas em nível executivo, gerenciará escalonamentos e promoverá proativamente a saúde da conta. Quem Você É: - Mais de 5 anos de experiência em uma função técnica voltada para o cliente em AdTech, Big Tech ou SaaS (Tech Account Manager ou TAM, Engenharia de Vendas ou Arquitetura de Soluções), com alguma exposição ao ecossistema mobile. - Obrigatório: Fluência profissional em inglês, português e espanhol. - Experiência comprovada em contas empresariais: Você gerenciou diretamente contas empresariais importantes, navegando em ambientes complexos de partes interessadas e atuando como um consultor técnico de confiança para contatos de clientes sêniores. - O Arquiteto Técnico: Especialista em traduzir requisitos de alto nível em especificações. Você se sente igualmente confortável discutindo a inicialização do SDK e a latência do ponto de extremidade REST com um Senior Product Owner como está depurando HTML/JavaScript. - Central Analítica: Proficiente em SQL e visualização de dados. Você tem ampla experiência no uso de painéis de análise como Grafana, Tableau, QuickSight ou Kibana para encontrar o "porquê" por trás dos números e tomar decisões técnicas estratégicas. - Nativo em Mobile & App: (Grande diferencial) Familiaridade com Java ou experiência na construção/suporte de aplicativos móveis com um "sexto sentido" para depurar problemas de integração de SDK. - Catalisador Multifuncional: Um colaborador natural que pode navegar pelas equipes internas de Engenharia e Produto para encontrar soluções em ambientes de alta pressão. - Desejável: Experiência com Desenvolvimento de Software. Combustível para a Jornada: Benefícios para Apoiar suas Ambições: - Plano de Saúde e Odontológico: Cobertura abrangente de saúde oferecida pela Care Plus (planos SOHO30 e ODONT20). - Seguro de Vida: Cobertura de seguro de vida e invalidez fornecida pela empresa para apoiar você e sua família. - Vale Refeição / Alimentação: Subsídio flexível mensal que pode ser usado em restaurantes, supermercados, serviços de entrega e muito mais. - Vale Transporte: Apoio mensal para ajudar a cobrir os custos de deslocamento. - Wellhub (Gympass): Acesso à plataforma Wellhub com descontos corporativos exclusivos em academias e serviços de bem-estar. - Programa de Assistência ao Empregado (EAP): O SupportLinc está disponível sem custo para você e sua família, oferecendo suporte e recursos confidenciais para promover o bem-estar e o equilíbrio entre vida pessoal e profissional. Por favor, envíe su CV en inglés We welcome applications from people who will contribute to the diversity of our company.

🔹Дорабатывать порталы и админку: новые разделы, отчёты, синхронизация данных между порталами. 🔹Развивать ботов на Python (Telegram и MAX, несколько клиентов на одной кодовой базе).

-Развивать DWH HR-отчетности: участвовать в проектировании и масштабировании корпоративного хранилища данных. -Интегрировать источники: собирать, очищать и консолидировать данные из учетных систем (в том числе SAP HCM/SAP BW).

As a Cyber Defense Engineer on our Cyber Defense Operations team, you will serve as a front-line defender responsible for protecting both BeyondTrust’s enterprise infrastructure and the integrity of the products our customers depend on. 4+ years of experience in a SOC, security operations, or incident response role.

Develop, maintain, and own key fraudulent CV models of Jumio, which shapes the whole fraud product offering of Jumio. Design and implement machine learning, deep learning, classical CV focused on fraud detection.

Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition). Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions.

• Own AI features from concept to production in a high-load environment (50k RPS, 450M users). • Work with LLMs and train purpose-built models for real-time applications.

Location: Remote, Canada; Remote, United States GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role As a Senior Backend Engineer on GitLab's Security Factory: Code Security team, you help developers find and fix security issues. Those issues live in the code they write and in the open source components they depend on. Your work spans complementary parts of a complete security analysis. On the dependency analysis side, you teach the analysis engine what a project depends on. You parse dependency manifests, lockfiles, and SBOMs so the engine knows which libraries and frameworks are in play and how the code uses them. You also extend the service that turns security advisories into automated merge requests that update vulnerable dependencies. On the vulnerability detection side, you grow GitLab's security analysis engine with hybrid analyzers that blend rule-based detection and AI reasoning. You build and apply the tooling that develops, evaluates, and ships those analyzers, and you measure how well they find real problems. That work also expands coverage of the libraries, frameworks, and AI agent tooling that real-world applications are built on. These threads reinforce each other. What a project depends on, and how its code uses those dependencies, are parts of one picture, and this team works across all of it. We make thoughtful use of AI-assisted development tools in our daily work. We expect you to use them effectively and with good judgment. What you do Act as the directly responsible individual (DRI) for team initiatives from design through delivery, shipping with minimal guidance in partnership with the technical lead Bring systems built by one engineer to team ownership through documentation, tests, and shared review Design and ship analyzers that pair deterministic analysis capabilities with AI-driven analysis, and build the evaluation harnesses that measure their false positives and missed findings against benchmark applications with known vulnerabilities, raising the bar for what counts as a trustworthy result. That includes detection rules mapped to CWE and the test fixtures that prove they work. Package those analyzers for every place GitLab runs them, including CI jobs, AI agent workflows, and command-line tools, with findings reported in GitLab's standard security report formats Design and ship the manifest, lockfile, and SBOM parsing that tells the static analysis engine what a project depends on, and extend it to new ecosystems and formats Ship features across the automated remediation service that turns security advisories into dependency update merge requests, from sandboxed updates to merge request creation Solve technical problems of high scope and complexity, actively seek out difficult impediments affecting the whole team, and advocate for improvements to quality, security, and performance with Product Management, Engineering stakeholders such as Frontend and UX, and partner teams such as Code Scanning and Composition Analysis Mentor Intermediate engineers through code review and pairing, and maintain our internal standards for style, maintainability, and best practices through review Participate in on-call rotations to assist troubleshooting product operations, security operations, and urgent engineering issues What you bring Experience building your own LLM tooling, such as a harness, an agent pipeline, or evaluations, with the judgment to know when output is trustworthy and when it isn't Substantial professional experience writing and testing production code in a systems language, particularly Go and/or Rust, with depth in at least one. We use both, plus Ruby on the remediation side and Python for some analyzers, and value willingness to work across them. Familiarity with package managers and dependency management in one or more language ecosystems, such as npm, Maven, pip, Bundler, or Cargo. Experience building tooling around them is better still. Demonstrated application security experience, such as vulnerability research, secure code review, or writing detection rules, and fluency with vulnerability classes (OWASP Top 10, CWE) and the software supply chain A track record of taking ownership of ambiguous problems and shipping with minimal guidance, with the self-motivation and organizational skills suited to a remote, largely asynchronous environment Demonstrated capacity to communicate clearly and concisely about technical problems, and to write design proposals that bring a team to a decision Helpful experience Experience evaluating AI-driven detection against labeled data, including measuring false positives and missed findings Experience with performance optimization at scale Hands-on program analysis experience, such as parsing, ASTs, or data-flow analysis Familiarity with popular web or mobile application frameworks and how they handle input, data, and configuration Experience with containerized workflows and CI/CD (we use Docker heavily) About the team The Security Factory: Code Security team builds GitLab's code-level security scanning capabilities, spanning static application security testing and dependency scanning. We help developers find and fix security issues in both the code they write and the open source components they depend on, as early as possible. We work closely with the Static Analysis team on GitLab's SAST engines, with Composition Analysis on the broader software supply chain, and with other groups across the Sec Section. We rely heavily on asynchronous work across time zones. Remote-Global The base salary range for this role’s listed level is currently for residents of the United States only. This range is intended to reflect the role's base salary rate in locations throughout the US. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, alignment with market data, and geographic location. The base salary range does not include any bonuses, equity, or benefits. See more information on our benefits and equity . Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary. United States Salary Range $139,200 — $235,200 USD How GitLab Supports Full-Time Employees Benefits to support your health, finances, and well-being Flexible Paid Time Off Team Member Resource Groups Equity Compensation & Employee Stock Purchase Plan Growth and Development Fund Parental Leave Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application. Country Hiring Guidelines: GitLab hires new team members in countries around the world. All of our roles are remote, however some roles may carry specific location-based eligibility requirements. Our Talent Acquisition team can help answer any questions about location after starting the recruiting process. Privacy Policy: Please review our Recruitment Privacy Policy. Your privacy is important to us. GitLab is proud to be an equal opportunity workplace and is an affirmative action employer. GitLab’s policies and practices relating to recruitment, employment, career development and advancement, promotion, and retirement are based solely on merit, regardless of race, color, religion, ancestry, sex (including pregnancy, lactation, sexual orientation, gender identity, or gender expression), national origin, age, citizenship, marital status, mental or physical disability, genetic information (including family medical history), discharge status from the military, protected veteran status (which includes disabled veterans, recently separated veterans, active duty wartime or campaign badge veterans, and Armed Forces service medal veterans), or any other basis protected by law. GitLab will not tolerate discrimination or harassment based on any of these characteristics. See also GitLab’s EEO Policy and EEO is the Law . If you have a disability or special need that requires accommodation , please let us know during the recruiting process .

Ищу Senior Data Engineer, который сможет взять на себя развитие нового DWH / Lakehouse-контура и стать владельцем хранилища данных end-to-end. — перенести текущую аналитику на новую Lakehouse-архитектуру;

Location: San Francisco, CA; Chicago, IL; Austin, TX; Atlanta, GA; Tampa, FL; Seattle, WA; Boston, MA; New York, NY; San Diego, CA; Washington DC; Los Angeles, CA Workplace: Remote 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 ROLE We’re hiring a Senior Technical Support Engineer to lead our customer support experience for highly technical users, from AI engineers to infrastructure architects. You’ll be on the front lines helping teams debug production LLM applications and agents, improve AI observability and evaluations, and unblock critical issues. You’ll also help define what world-class technical support looks like for modern AI platforms KEY RESPONSIBILITIES - Be the go-to escalation point for technical support inquiries—diagnosing issues across customer setup, LangChain products, and deployment issues. - Work directly with engineering, operations, documentation, and product teams to resolve bugs, suggest patches, and advocate for customer needs. - Partner with Deployed Engineering to support critical enterprise customers. - Build and refine internal tooling, diagnostics, and runbooks for complex issue triage. - Lead post-mortems for critical incidents and feed learnings back into product and documentation. - Help refine KPIs for support health (MTTR, CSAT, bug recurrence) and drive continuous improvement. - Improve documentation and knowledge articles to improve 1-to-many resources and provide proactive support. - Mentor and coach other support engineers. HOW TO BE SUCCESSFUL IN THIS ROLE - 6+ years in technical support, solutions engineering, or SRE roles in deeply technical B2B environments (e.g., observability, infrastructure, data platforms). - Expert troubleshooting skills across APIs, SDKs, distributed systems, and cloud-native stacks. - Programming experience with Python. Bonus if you have TypeScript experience. - Hands-on knowledge of Kubernetes and Docker - Comfort working with logs, traces, metrics in Datadog, and 3rd-party integrations (e.g., OpenTelemetry, LLM providers). - Experience supporting enterprise customers and collaborating with engineering on complex escalations. - A bias for clarity and continuous improvement: you write succinct, helpful, and accurate responses and build a foundation for case deflection. - High ownership — want to do what’s best for the customer and the company and are relentlessly results oriented Location: Remote COMPENSATION - Annual salary range: $130,000 - $195,000 USD + equity 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: Atlanta, GA; Austin, TX; Dallas, TX; Las Vegas, NV; Nashville, TN; Seattle, WA; Boston, MA; Detroit, MI; San Diego, CA; Denver, CO Workplace: Remote 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 ROLE We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION Remote COMPENSATION $150,000-$270,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Hybrid 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 ROLE We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION San Francisco, CA COMPENSATION $150,000-$300,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Hybrid 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 ROLE We're looking for a Deployed Engineer to join our Professional Services team, working directly with enterprise customers to build reliable, production agents. You'll translate vague enterprise workflows into concrete software specs and guide engineering teams through the resulting solution, or build it for them. You might spend a week designing a customer's agent architecture, a few weeks co-building their evaluation pipeline, or a quarter embedded inside their team shipping alongside their engineers. You are someone who's built real AI systems for production and can defend the technical tradeoffs within them. KEY RESPONSIBILITIES - Advising: Agent architecture design, evaluation strategy review, and best-practice production guidance. - Building: Co-build with the customer's engineering team across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements. - Embedding: Serve as a deployed engineer inside the customer's team for extended engagements, operating as a de facto member of their org to ship agent systems directly. - Agent Engineering: ADLC end-to-end, architecture design, orchestration patterns, evals, custom conversational UIs, and production deployment. - Applied AI: Post-training, supervised fine-tuning, harness engineering, trace mining, model selection and evaluation methodology. REQUIREMENTS - 4+ years of software engineering experience with deep expertise in Python. TypeScript/JavaScript a plus. - 2+ years of hands-on experience building and shipping production agent systems. - Strong client-facing communication skills, with the ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs). - Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory). - Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems. - Comfortable operating across the full spectrum from advisory to embedded delivery. - Willing to travel up to 20% of the time. NICE TO HAVE - Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL. - Experience with trace mining to drive continuous improvement loops LOCATION New York, New York COMPENSATION $150,000-$300,000 base + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: New York City Compensation: $170,000-$300,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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: Austin, TX Workplace: Remote 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 ROLE We're looking for a Deployed Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems. This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains. This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture. KEY RESPONSIBILITIES - Infrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelines - Agent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operations - Customer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teams WHAT WE'RE LOOKING FOR REQUIRED EXPERIENCE 7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to apply Infrastructure & Platform: - 3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure) - Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deployments - Experience with Infrastructure as Code (Terraform, Helm) and GitOps practices - Knowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizing - Experience designing high-availability and disaster recovery solutions - Strong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog) - Experience with CI/CD pipelines for infrastructure and applications Agent Engineering & Development: - 1+ years of experience building production AI/ML applications or agents - Strong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applications - Experience with state management patterns (short-term and long-term memory) - Experience designing and implementing evaluation frameworks for AI applications - Strong prompt engineering skills with experience in optimization and A/B testing - Experience with vector stores, RAG patterns, and knowledge organization - Experience with tool integration, API design, and error handling patterns - Strong Python and/or TypeScript development skills Customer-Facing: - Customer-facing experience with enterprise customers - Experience conducting technical assessments or infrastructure audits - Strong communication skills with ability to explain technical concepts to diverse audiences KEY ATTRIBUTES - Strong problem-solving skills with ability to analyze complex requirements and design elegant solutions - Excellent customer-facing communication skills, able to explain technical concepts to diverse audiences - Experience working cross-functionally with engineering teams, product teams, and customers - Consultative approach with ability to understand customer needs, provide recommendations, and guide implementation - Ability to balance infrastructure architecture with agent development work - Strong engineering background with hands-on development experience - Willing to travel up to 20% of the time Location: Austin, Texas Compensation: $170,000-$270,000 base salary + equity Looking to lead technical strategy across the customer journey from Proofs of Value (PoVs) to driving overall adoption? Please check out the Deployed Engineer listing focused on Account Strategy & Solutions. 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.