Responsibilities
- 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.
Requirements
- 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
- 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.
Benefits
- medical, dental, and vision coverage
- flexible vacation
- a 401(k) plan
- life insurance
- meals on in-office days in the US
Work Arrangement
Hybrid
Team
Structure: The Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.
Additional Information
- This role requires up to 40% travel to customer sites to support deployment, onboarding, and ongoing technical engagement.
