Jobs at LangChain

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.

Drive adoption of LangChain products by supporting the full sales cycle from outreach through close. Build relationships with technical prospects and customers, understand their needs, prospect strategically across SMB, mid-market, and small-enterprise accounts, and source, qualify, and close outbound deals. The role requires urgency, curiosity about GenAI technology, strong follow-through, resourcefulness, and collaboration with sales, engineering, and customer success teams.

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.

Own onboarding for new LangSmith customers from kickoff through early activation, including administration, SDK integration, tracing, evaluations, and LangGraph deployment. Guide customers through security and production-readiness topics, coordinate with internal teams to resolve issues, develop onboarding documentation and runbooks, and track activation metrics. Help customers independently build evaluation workflows and debug production traces.

The Deployed Engineer collaborates with customer teams to co-architect and deploy production AI agents, guiding technical evaluations and sharing feedback to improve outcomes.

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.

Own and manage the sales cycle, acting as a trusted advisor to customers, driving proof-of-concept efforts, and building relationships to support post-sale success.

Collaborate with customer engineers to design and deploy AI agents in production. Provide technical guidance, conduct training, and ensure successful outcomes for customers.

Own technical sales wins by leading discovery, evaluations, architecture reviews, proofs of concept, demos, and competitive assessments. Co-architect and build production AI agents with customers, support deployments, provide post-sale technical guidance, and identify expansion opportunities. The role also includes customer training, reusable technical content, upstream contributions, and sharing field feedback with product teams.

Own the full enterprise software sales cycle from lead generation through close. Build trusted relationships with technical decision-makers, lead proof-of-concept efforts, communicate product value, negotiate pricing and contracts, and support post-sale success. Collaborate with engineering, product, customer success, deployment, and legal teams while contributing customer insights and helping develop LangChain’s sales playbook and go-to-market strategy.

Own the full enterprise sales cycle for LangChain’s AI products, from lead generation through contract negotiation and close. Build trusted relationships with technical decision-makers, lead proof-of-concept efforts, communicate product value, and support post-sale success. Collaborate with sales engineering, product, engineering, legal, deployment, and support teams while providing customer feedback and helping develop the company’s sales playbook and go-to-market strategy.

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.

This role involves managing the full sales cycle, building relationships with enterprise clients, driving product adoption, and collaborating with internal teams to enhance customer success and experience.

As a Solutions Architect, design and deploy scalable AI infrastructure, optimize applications, lead customer assessments, and enhance technical best practices.

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.