About The Role
We’re hiring fullstack Applied AI Engineers to help us build AI agents that power every part of LangChain from Marketing and GTM to Recruiting, Support, Internal Tools, and our Core Product. In this role you will own a problem space and work closely with that function to design, build, and deploy production-grade agents, workflows, and applications that transform how we operate. Your work will directly accelerate LangChain’s mission to make intelligent, autonomous software a reality both internally and for our customers. Some of these projects will be open source, contributing to the LangChain and LangGraph ecosystem and setting new standards for how companies build with AI.
What You Will Do
- Design, implement, and deploy end-to-end AI workflows and agents that solve real problems across multiple business domains.
- Develop and iterate on agent architectures, evaluation pipelines, and performance frameworks to ensure reliability and measurable outcomes.
- Translate emerging AI research and tooling into practical, production-ready solutions.
- Communicate technical decisions, trade-offs, and insights clearly to both technical and non-technical stakeholders.
- Collaborate cross-functionally embedding with teams like Marketing, GTM, Recruiting, or Product to identify opportunities for agent-driven automation and measurable business impact.
- Contribute to the LangChain and LangGraph ecosystem, including open source components, documentation, and shared tools.
What You Will Bring
- Experienced software engineer with a strong track record shipping AI or ML-powered applications (typically 3+ years, including at least 1 year building LLM systems in production).
- Hands-on experience implementing evaluation and monitoring systems for agents or workflows.
- Deep understanding of the components that make up an AI system: prompting, retrieval, orchestration, inference APIs, and model selection across modalities.
- Strong coding skills in Python or TypeScript (ideally both).
- Excellent communicator who can simplify complex technical ideas for diverse audiences.
- Thrives in a fast-moving, ambiguous startup environment; enjoys identifying the highest-impact problems and driving them to completion.
- Naturally curious and motivated to learn new tools, frameworks, and approaches in applied AI.
Nice To Haves
- Expertise with LangChain or LangGraph.
- Experience building or maintaining open source projects.
- Background in applied AI research or agentic workflow development.