Deployed Engineer (Atlanta)

Atlanta, GAfull timeOn Site

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mid

$150k–$250k

H1B: no

Langchain The Deployed Engineer at LangChain works hands-on with customer engineering teams to co-architect and build production AI agents, focusing on technical wins and reliable operation at scale. This role bridges engineering, product, and go-to-market functions to shape LangChain’s adoption and platform feedback.

Responsibilities

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.
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
What You’ll Bring
3+ 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

Qualification

You’ve deployed AI agents in productionWorked with LLM evaluation

Preferred

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