About Us

At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.

With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.

Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.

About The Team:

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, while also building internal agents that power LangChain’s own GTM and engineering workflows. It’s a small, fast-moving team that operates at the frontier, iterating rapidly, running rigorous evals on our own work, and feeding hard-won learnings back into the platform. If you want to work on the frontier of agent-building, this may be the team for you.

About The Role:

We’re looking for a Lead Applied AI Engineer based in our NYC office. This is a hands on role leading technical projects end to end and mentoring other engineers. You will help drive the development of complex agentic projects.

You’re expected to build, ship, and also be the person other engineers come to when a project is stuck or a design decision needs a second set of eyes.

• This role is based onsite in New York, NY

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
• 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 openView Posting source components, documentation, and shared tools.

What You’ll Bring:

• 4+ years of software engineering experience with direct experience building and deploying LLM-powered applications or agents in production
• Experience leading technical projects end to end, mentoring engineers and raising the technical quality of a team
• 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.
• Based in or willing to relocate to New York, NY

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