Jobs at LangChain

Leads and scales LangChain’s SDR team by owning performance, coaching, recruiting, pipeline generation, qualification playbooks, and productivity systems. Partners with sales, marketing, and RevOps to improve inbound and outbound motions, target-account alignment, conversion rates, and revenue pipeline. The role requires strong data-driven management, technical product familiarity, modern GTM tooling experience, and the ability to develop early-career sales talent in a rapidly evolving environment.

Design scalable AI infrastructure, build agent applications, engage with enterprise customers for requirements, and optimize deployment strategies. Work with cross-functional teams to implement solutions.

Build and operate the LangSmith Deployments runtime for long-running AI agents: design distributed queue/worker systems, own state persistence and job claiming, implement resumable streaming, instrument production systems, participate in on-call and incident response, produce system documentation, and contribute to open-source LangGraph.

The role involves designing and optimizing a storage layer for AI observability, coding in Rust, and ensuring efficient database performance.

Qualify inbound and outbound prospects via phone, email, and LinkedIn, hand off opportunities to Account Executives, capture prospect insights to inform sales and product, and experiment with channels and LangChain-powered agents to improve outreach and conversion.

Build and own LangChain’s React component library and design system. Develop accessible, reusable UI components; translate design tokens and interaction patterns into code; create tooling for theming, versioning, testing, visual regression, and component discovery; and optimize build performance, bundling, dependency management, and package versioning. Collaborate closely with designers, product engineers, and platform teams to maintain a consistent, high-quality frontend foundation.

Work directly with customers to co-architect, build, deploy, and operate production AI agents. Lead pre-sales technical evaluations and POCs, run demos and workshops, advise on architecture and best practices, contribute reusable patterns and occasional code, and travel to customer sites to support deployments.

As a Backend Engineer, you will design and build backend systems and APIs for LangChain's observability and evals platform, optimizing performance and reliability while collaborating with cross-functional teams.

Own Salesforce-centered GTM systems programs from discovery through UAT, deployment, change management, and adoption. Translate ambiguous revenue-team needs into specifications, process flows, data models, acceptance criteria, and prioritization decisions. Manage sales process redesign, vendor evaluations, revenue-data integrity, and reconciliation across Salesforce, billing, and cloud marketplaces. Partner across Sales, Marketing, Partnerships, Support, Finance, engineers, and AI coding agents while maintaining quality and release-risk controls.

Own the infrastructure, deployment, and operational reliability of SmithDB, a distributed database for AI observability. Responsibilities include Kubernetes and cloud cluster management, infrastructure as code, CI/CD, upgrades, failover, incident response, SLOs, disaster recovery, capacity planning, cost optimization, and production rollouts across AWS, GCP, and Azure. The role partners with database engineers to safely deploy engine improvements at large scale.

Own onboarding for new LangSmith customers, guiding them from kickoff through admin setup, SDK integration, first traced run, evaluations, and LangGraph deployment. Help customers address security, organization design, workload isolation, integrations, and production readiness. Coordinate with GTM, Product, Engineering, and specialists to resolve issues, create repeatable onboarding resources, and track activation metrics such as time to first trace and production run.

Lead a small systems team building SmithDB: write and review Rust production code, make architecture decisions for storage and query execution, drive performance profiling and fixes, deploy and harden distributed Kubernetes services, integrate cloud object stores, build observability, and manage hiring, mentorship, and the technical roadmap.

Create industry and use-case solution narratives that map LangChain's platform to enterprise buyer needs. Develop sales enablement, campaign assets, and repeatable sales plays; partner with sales, product, field marketing, and customer teams to drive pipeline and enable complex buying committees for production-ready AI agents.

Lead product and solutions marketing for Fleet: positioning, launches, content, enablement, campaigns, and enterprise solutions. Translate technical capabilities into customer narratives, build sales enablement, partner with product, sales, and demand generation, and develop industry-specific programs to drive awareness, adoption, and revenue.

Design developer-focused product experiences across LangChain's platform. Conduct user research with developer teams, own end-to-end feature design from concept to shipped UI, solve complex interaction problems for dense technical data, and collaborate closely with product and engineering to iterate quickly.

Develop and maintain benchmarks, run experiments across models, prompting, tools, and orchestration, and implement fine-tuning or post-training improvements. Analyze production agent failures, optimize for cost/latency/reliability, and ship measurable production improvements while guiding ML roadmap and mentoring teammates.

Provide commercial legal support across sales, partnerships, vendor, and operational contracts. Draft, review, and negotiate MSAs, DPAs, security addenda, vendor agreements, and partner deals. Advise cross-functional teams on privacy, security, IP, AI/LLM usage, and risk. Build contracting templates, playbooks, intake workflows, and help implement Ironclad to scale legal operations.

Partner Engineer builds reference architectures, integrations, and enablement for cloud providers and systems integrators. Owns partner certification, workshops, delivery playbooks, and joint technical roadmaps. Acts as technical evangelist, escalation point for partner deployments, and relays partner feedback to product and engineering.

Write and maintain developer-focused product documentation (user guides, API docs, specs). Collaborate with engineering, product, and support teams to ensure clarity and accuracy, improve documentation standards and processes, review content, and continuously update docs as products evolve.

Build and ship production-grade autonomous customer agents using LangChain/LangGraph to deflect support cases and automate onboarding. Own technical roadmap, design agentic architectures, dogfood the stack, and deliver end-to-end AI-native onboarding and self-service systems.