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 platform.
ABOUT THE ROLE
The Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
This will be a hybrid in office role in Chicago, IL.
WHAT YOU’LL DO
Co-architect and co-build production AI agents with customer engineering teams
Own the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluations
Help customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflows
Advise customers post-sale on architecture, best practices, and roadmap-level decisions
Run technical demos, trainings, and workshops for developer audiences
Surface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customers
Occasionally contribute code upstream when it meaningfully improves customer outcomes
Travel to customers up to 25% of the time
WHAT YOU’LL BRING
6+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-up
Strong Python, JavaScript and systems fundamentals
Have designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handling
Are comfortable working directly with customers during POCs, architecture reviews, and technical evaluations
Can explain technical tradeoffs clearly and build trust with developer audiences
Take responsibility for outcomes, not just recommendations
Have a bias toward action and enjoy figuring things out as you go
Are excited about operating AI agents in production, not just building demos
NICE TO HAVE’S
You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
Worked with LLM evaluation, observability, or guardrails
Have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
Have shipped and operated production software and are comfortable owning systems under real-world constraints
COMPENSATION
Annual OTE range: $200,000–$300,000 USD. Final compensation will depend on experience, skills, and location.
Looking for a hands-on implementation role focused on custom delivery, bespoke integrations, and scoped consulting projects? Please check out the Deployed Engineer (Professional Services) roles.
Compensation Philosophy
We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
BENEFITS
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.
