The opportunity
The Applied AI team builds the agents that show the world what's possible with LangChain. We ship open source reference agents like Open SWE, Open Canvas, and our Deep Research agent that developers across the community use as starting points for their own production systems,…
What you'll 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
Set the technical bar for the team on code quality, testing, documentation, and project scoping
Mentor engineers on the team through code review and design discussions
Work directly with customers and internal stakeholders to translate requirements into technical plans
Identify gaps in internal tooling, frameworks, and processes and drive enhancements
What they're looking for
- 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 View: Posting source components, documentation, and shared tools.
- + years of software engineering experience with direct experience building: and deploying LLM-powered applications or agents in production
