Deployed Engineer (Early Career-NYC)
HotApplication analysis
Deployed Engineer (Early Career-NYC) at LangChain is a forward deployed llm tooling role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Technical customer-facing role role centers on hands-on work with customers to ship and adopt technical products.
About LangChain
LangChain builds frameworks and products for production LLM applications with a deeply technical user base. The role is anchored in New York, NY, so expect on-site customer work in that region.
Stand out for Deployed Engineer (Early Career-NYC)
- Lead your application with one paragraph tying Deployed Engineer (Early Career-NYC) to a specific customer or deployment you owned — LangChain hires for shipped outcomes, not tool lists.
- Mirror language from the job description in your examples — if they emphasize deployment, use deployment stories; if integration, use integration stories.
- Include a short “how I work with customers” section in your cover note: communication cadence, escalation instincts, and how you handle ambiguity.
- This role is tied to New York, NY — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at LangChain
- Demonstrate LLM app architecture with a concrete example — LangChain will probe for specifics, not buzzwords.
- Demonstrate open-source community fluency with a concrete example — LangChain will probe for specifics, not buzzwords.
- Contributions to LangChain/LangGraph or a public agent project is high-signal here.
- Read recent engineering blog posts, product launches, and customer stories on langchain.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
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 This team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on. This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite. Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the pl