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Drive adoption of LangChain products by managing the full sales cycle for SMB to small-enterprise accounts: prospect, build relationships, qualify needs, and close deals. Collaborate with sales, engineering, and customer success teams to support technical evaluations and accelerate customer onboarding.

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.

The Senior Backend Engineer will enhance the security and scalability of the LangChain platform, working on enterprise readiness features such as authentication and billing systems while collaborating with various teams and enterprise clients.

Own and scale high-throughput ingestion and trace-query systems, define SDK/CLI/API standards, build and maintain integrations, debug performance and distributed-system issues, run monitoring/alerting and participate in on-call incident response to ensure reliable observability and developer-facing surfaces.

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 the full enterprise sales cycle for LangChain products, build trusted customer relationships, drive proofs-of-concept, negotiate deals and contracts, collaborate with engineering/product/customer success, and feed customer insights into product roadmap to accelerate GenAI adoption.

The Solutions Architect will design and optimize AI infrastructure and agent systems, ensuring high availability and performance for enterprise customers. Responsibilities include infrastructure engineering, agent application development, and customer engagement.

Collaborate with customer engineering teams to co-architect and build AI agents, run demos, and advise on architecture and best practices post-sale.

Lead and scale LangChain's content practice: define strategy and roadmap, hire and mentor a content team, own flagship initiatives and blog performance, write and edit key content, expand SEO/AEO efforts, build editorial standards and workflows, collaborate cross-functionally, and measure/optimize content impact.

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.