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LangChain is seeking a Deployed Engineer for its Professional Services team in APAC to work directly with enterprise customers building production-ready AI agents. You will translate enterprise workflows into concrete software specifications and guide or co-build solutions with customer engineering teams.
In this role, you will:
- Advise on agent architecture design, evaluation strategy, and production best practices for enterprise customers
- Co-build with customer engineering teams across the full Agent Development Lifecycle (ADLC) in outcome-scoped engagements
- Serve as an embedded engineer within customer teams for extended engagements, operating as a de facto team member to ship agent systems
- Design and implement end-to-end agent engineering solutions including architecture, orchestration patterns, evaluation frameworks, custom conversational UIs, and production deployment
- Apply advanced AI techniques including post-training, supervised fine-tuning, harness engineering, trace mining, and model selection/evaluation methodology
You will work with Fortune 500 companies (LangChain's customers include Klarna, Coinbase, Workday, Lyft, Cloudflare, and others) on complex, high-impact agent deployments. Engagements range from week-long architecture design sprints to quarter-long embedded team assignments.
LangChain is a Series B company (raised $125M from IVP, Sequoia, Benchmark, CapitalG, Sapphire Ventures) with 100M+ monthly open-source downloads and 6,000+ active LangSmith customers. The platform includes LangSmith (observability, evaluation, deployment, fleet, sandboxes), open-source frameworks (LangChain, LangGraph, Deep Agents), and LangSmith Engine for autonomous agent improvement.
REQUIREMENTS:
- 4+ years of software engineering experience with deep expertise in Python (TypeScript/JavaScript a plus)
- 2+ years of hands-on experience building and shipping production agent systems
- Strong client-facing communication skills; ability to confidently articulate architectural decisions to technical stakeholders (engineers, architects, CTOs)
- Strong experience with LangChain/LangGraph/Deep Agents or comparable frameworks, including multi-agent patterns and state management (short and long-term memory)
- Deep familiarity designing and implementing evaluation methodologies for non-deterministic AI systems
- Comfortable operating across the full spectrum from advisory to embedded delivery
- Willing to travel up to 20% of the time
NICE TO HAVE:
- Exposure to dataset curation and post-training techniques (SFT, DPO, RLHF) on open-weight models using tools like Axolotl, Unsloth, Hugging Face transformers, or TRL
- Experience with trace mining to drive continuous improvement loops
About LangChain
AI / Data / Infrastructure — developer platform and framework for building LLM applications and agents.
