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Drive adoption of LangChain’s AI products by sourcing, qualifying, and closing outbound mid-market deals. Build relationships with technical teams, help prospects evaluate solutions, and collaborate with sales, engineering, and customer success teams. The role requires curiosity about GenAI technology, strong execution in a fast-paced environment, and resourcefulness in advancing customer opportunities.

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

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.

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.

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.

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.

The People Partner will embed with teams to drive business outcomes, proactively address organizational challenges, and implement AI-driven people solutions.

Build and enhance LangSmith frontend features: implement user-facing UI with React and TypeScript, create reusable components, translate designs into high-quality code, optimize performance, and collaborate with backend engineers and designers to improve observability and evaluation workflows for LLM applications.