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TL;DR
Deployed Engineer (AI) (LangChain, LangGraph, Python): Building reliable production AI agents and agent systems for enterprise customers with an accent on architecture design, evaluation methodologies, and end-to-end deployment. Focus on translating ambiguous workflows into software specifications, co-building evaluation pipelines, and applying post-training and trace mining to improve non-deterministic systems.
Location: Remote within the United States; listed locations include Atlanta, Austin, Boston, Dallas, Denver, Detroit, Las Vegas, Nashville, San Diego, and Seattle.
Salary: $150,000–$215,000 base annually, plus equity.
Company
LangChain develops open-source frameworks and the LangSmith platform for building, evaluating, deploying, and operating AI agents at scale.
What you will do
- Advise enterprise customers on agent architecture, evaluation strategies, and production best practices.
- Translate ambiguous enterprise workflows into concrete software specifications and technical solutions.
- Co-build production agent systems with customer engineering teams across the Agent Development Lifecycle.
- Embed with customer teams for extended engagements and ship agent systems alongside their engineers.
- Design orchestration patterns, multi-agent systems, memory, conversational UIs, evaluations, and production deployments.
- Apply post-training, supervised fine-tuning, harness engineering, trace mining, model selection, and evaluation methodologies.
Requirements
- 4+ years of software engineering experience with deep expertise in Python.
- 2+ years of hands-on experience building and shipping production agent systems.
- Strong client-facing communication skills and the ability to explain architectural decisions to technical stakeholders.
- Strong experience with LangChain, LangGraph, Deep Agents, or comparable frameworks, including multi-agent patterns and short- and long-term memory.
- Deep familiarity with evaluation methodologies for non-deterministic AI systems.
- Ability to work across advisory, co-building, and embedded delivery engagements.
Nice to have
- TypeScript or JavaScript experience.
- Experience with dataset curation and post-training techniques such as SFT, DPO, and RLHF.
- Experience with Axolotl, Unsloth, Hugging Face Transformers, or TRL.
- Experience using trace mining to drive continuous improvement loops.
Culture & Benefits
- Remote work with a customer-facing, embedded delivery model.
- Meaningful equity and competitive compensation.
- Medical, dental, and vision coverage.
- Flexible vacation.
- 401(k) plan and meals on in-office days in the US.
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