Deployed Engineer, Professional Services (San Francisco)
San Francisco · USD 150,000-300,000 · 2+ years experience · Full-time · Hybrid · Posted Oct 9, 2026
At a glance
- Experience
- 2+ years experience
- Employment
- Full-time
- Workplace
- Hybrid
- Location
- San Francisco
- Salary
- USD 150,000-300,000 · Base salary
About LangChain
- 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 role
- The Deployed Engineer in Professional Services works directly with enterprise customers to build reliable, production-ready AI agents.
- This role involves translating complex enterprise workflows into technical specifications and either guiding customer engineering teams or building solutions alongside them.
- Responsibilities range from designing agent architectures and evaluation pipelines to embedding within customer teams for extended periods.
Responsibilities
- Advise on agent architecture design, evaluation strategy, and production best practices.
- Co-build agent solutions with customer engineering teams across the full Agent Development Lifecycle (ADLC).
- Serve as an embedded engineer within customer organizations to ship agent systems directly.
- Execute end-to-end ADLC, including orchestration patterns, custom conversational UIs, and production deployment.
- Apply AI techniques including post-training, supervised fine-tuning, harness engineering, trace mining, and model selection.
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 for technical stakeholders.
- Experience with LangChain, LangGraph, Deep Agents, or comparable frameworks.
- Knowledge of multi-agent patterns and state management.
- Deep familiarity with evaluation methodologies for non-deterministic AI systems.
- Ability to operate across the spectrum from advisory to embedded delivery.
- Willingness to travel up to 20% of the time.
Preferred qualifications
- Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models.
- Experience with tools like Axolotl, Unsloth, Hugging Face transformers, or TRL.
- Experience with trace mining to drive continuous improvement loops.
Benefits
- Medical coverage
- Dental coverage
- Vision coverage
- Flexible vacation
- 401(k) plan
- Meals on in-office days (US)
Workplace
- Willing to travel up to 20% of the time.
Skills
- Python
- TypeScript
- JavaScript
- LangChain
- LangGraph
- Deep Agents
- Axolotl
- Unsloth
- Hugging Face Transformers
- TRL
