Deployed Engineer
Work directly with customers to co-build, deploy, and operate production AI agents using LangChain tools. Own technical pre-sales wins through POCs and evaluations, provide post-sale architecture advice, and contribute reusable patterns while traveling 40% to customer sites. Requires 3+ years technical experience, strong Python/JS fundamentals, and hands-on LLM application design.
About the job
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
- This role requires 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement
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
- 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: $155,000 - $165,000+ (depending on experience)
Skills
Python, JavaScript, LLMs, LangChain, LangGraph, AWS, GCP, Azure, Kubernetes, Observability, Guardrails
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