Deployed Engineer (NYC)
About the role
The Deployed Engineer will work on some of the hardest problems in applied AI, not demos or research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.
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
- Advises 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
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
Are excited about operating AI agents in production, not just building demos
Qualifications
Nice to have:
- You’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworks
- You’ve worked with LLM evaluation, observability, or guardrails
- You have experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes concepts
- You have shipped and operated production software and are comfortable owning systems under real-world constraints
Skills
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
Are excited about operating AI agents in production, not just building demos
Benefits
Annual OTE range: $165,000–$380,000 USD
Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks.
Actual compensation and offerings will vary based on role, level, and location.
Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.
Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.