LangChain
Deployed Engineer (NYC)
About this role
LangChain seeks a Deployed Engineer to work directly with enterprise customers building production AI agents. You'll co-architect agent systems, lead technical evaluations and POCs, and help customers deploy and operate agent-based applications at scale using the LangChain platform.
What you'll do
- Co-architect and build production AI agents alongside customer engineering teams
- Own technical wins in pre-sales by designing POCs and guiding evaluations
- Deploy and advise customers on agent-based applications including conversational and multi-step workflows
- Conduct technical demos, trainings, and workshops for developer audiences
- Surface field feedback and develop reusable patterns and example code
- Provide post-sale architecture guidance and advise on roadmap decisions
What they're looking for
- Python and JavaScript programming
- Agent-based and LLM application design
- Systems architecture and fundamentals
- Customer-facing technical engagement
- Technical communication and explanation of tradeoffs
- Cloud environments (AWS, GCP, Azure)
- LangChain/LangGraph frameworks
- LLM evaluation and observability
Benefits
- Annual OTE: $165,000–$380,000 USD
- Work on production AI systems with Fortune 500 companies
- Direct impact on product direction and real-world AI adoption
- Backed by $125M Series B funding (IVP, Sequoia, Benchmark, others)
- Hands-on technical role with fast feedback loops
- NYC-based position
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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
- Can you walk us through a production AI agent or LLM-powered system you've built? What were the hardest operational challenges you faced, and how did you solve them?
- Tell us about a time you worked directly with a customer or stakeholder to design a technical solution. How did you handle disagreement on architecture or tradeoffs?