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Deployed Architect, Professional Services (NYC)

$170k - $215k

LangChain

About UsAt 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 RoleWe'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 ResponsibilitiesInfrastructure & 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 pipelinesAgent 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/operationsCustomer 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 teamsWhat We're Looking ForRequired Experience7+ 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 applyInfrastructure & 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 deploymentsExperience with Infrastructure as Code (Terraform, Helm) and GitOps practicesKnowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizingExperience designing high-availability and disaster recovery solutionsStrong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog)Experience with CI/CD pipelines for infrastructure and applicationsAgent Engineering & Development:1+ years of experience building production AI/ML applications or agentsStrong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applicationsExperience with state management patterns (short-term and long-term memory)Experience designing and implementing evaluation frameworks for AI applicationsStrong prompt engineering skills with experience in optimization and A/B testingExperience with vector stores, RAG patterns, and knowledge organizationExperience with tool integration, API design, and error handling patternsStrong Python and/or TypeScript development skillsCustomer-Facing:Customer-facing experience with enterprise customersExperience conducting technical assessments or infrastructure auditsStrong communication skills with ability to explain technical concepts to diverse audiencesKey AttributesStrong problem-solving skills with ability to analyze complex requirements and design elegant solutionsExcellent customer-facing communication skills, able to explain technical concepts to diverse audiencesExperience working cross-functionally with engineering teams, product teams, and customersConsultative approach with ability to understand customer needs, provide recommendations, and guide implementationAbility to balance infrastructure architecture with agent development workStrong engineering background with hands-on development experienceLocation: New York CityCompensation: $170,000-$215,000 base salary + equity Compensation Philosophy:We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

Vacancy posted 2 days ago
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