LangChain
Fullstack Software Engineer, Applied AI
About this role
LangChain is seeking a Fullstack Applied AI Engineer to design and deploy production-grade AI agents and workflows across the company's operations and open-source ecosystem. You'll work at the frontier of agent engineering, collaborating with cross-functional teams to build autonomous systems that accelerate LangChain's mission while contributing to widely-used frameworks like LangChain and LangGraph.
What you'll do
- Design and deploy end-to-end AI workflows and agents solving real problems across multiple business domains
- Develop agent architectures, evaluation pipelines, and performance frameworks to ensure reliability
- Translate emerging AI research into practical, production-ready solutions
- Collaborate with cross-functional teams (Marketing, GTM, Recruiting, Product) to identify automation opportunities
- Contribute to LangChain and LangGraph ecosystem including open source components and documentation
- Communicate technical decisions and trade-offs to technical and non-technical stakeholders
What they're looking for
- Python or TypeScript (ideally both)
- LLM systems and production AI applications
- Evaluation and monitoring systems for agents
- Prompting, retrieval, orchestration, and model selection
- Agent architecture and workflow design
- Clear technical communication
- Fast-paced startup problem-solving
- Curiosity about emerging AI tools and frameworks
Benefits
- Work at the frontier of agent engineering and AI research
- Contribute to widely-adopted open-source projects (100M+ monthly downloads)
- Meaningful impact on company direction and product development
- 5-day in-office work in San Francisco or New York (hybrid eligibility based on location)
- Opportunity to ship production systems used by Fortune 500 companies
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LangChain
LangChain builds platforms and frameworks for developing, deploying, and observing production AI agents at enterprise scale, including LangSmith for AI observability and evaluation. The company is hiring Deployed Engineers to work directly with enterprise customers on agent implementation and operations, as well as Fullstack Engineers to build features across its platform stack.
- Website
- langchain.com
Likely interview questions
- Tell us about a production LLM system you've built. What were the biggest challenges in going from prototype to production, and how did you address reliability and performance?
- Walk us through your experience building evaluation and monitoring systems for AI agents or workflows. How do you measure whether an agent is actually working as intended?