Job Description
The Role
You’ll own the full technical lifecycle of customer AI agent deployments, from first integration to live monitoring, working at the intersection of product, engineering, and customer outcomes. This role is for engineers who use AI to compress timelines, ship higher-quality work, and want their impact felt immediately, not six months from now.
You Might Be This Person If
- You think in systems — inputs, outputs, failure modes — and you naturally ask “what happens when this breaks?” before anyone else does
- You’ve debugged something live, under pressure, with a customer watching, and you didn’t flinch
- You use AI tools daily to prototype, debug, and iterate, and you’ve figured out how to get 10x the output without cutting corners on quality
- You read a system prompt the way a compiler reads code, spotting logic gaps, unintended behaviors, and edge cases others miss
- You’ve built something end-to-end, frontend to backend to deployment, and you’re proud of how it actually held up
- You learn fastest by building, not by reading docs, and you’ve shipped something with a new API within days of touching it for the first time
- You care about what the customer actually experiences, not just whether the tests pass
- Ambiguity doesn’t slow you down. You’d rather build a rough solution and iterate than wait for a perfect brief
You Need To Have
- 2-3 years of hands-on software engineering experience in full-stack or backend development
- Strong Python proficiency and the ability to write clean, maintainable code under real-world constraints
- Practical experience with React and modern JavaScript/TypeScript on the frontend, plus backend frameworks like Node.js, Django, or Express
- Hands-on experience with LLM APIs (e.g., OpenAI, Claude) or agent frameworks such as LangChain
- Familiarity with RAG pipelines, knowledge base integration, and cloud deployment platforms (e.g., AWS Lambda, Vercel, GCP Cloud Functions)
What You’ll Actually Do
- Deploy production-grade AI agents tailored to each customer’s environment, owning setup, configuration, and go-live
- Tune system prompts and agent behaviors against real-world use cases, using AI-assisted workflows to move from hypothesis to working solution faster than a traditional dev cycle allows
- Prototype and ship fast, leveraging agentic coding tools to build agent interfaces, dashboards, and backend integrations with Next.js, React, and modern APIs
- Integrate RAG pipelines and knowledge bases that give agents the context they need to perform
- Monitor live deployments with logging, metrics, and observability so issues surface before customers notice them
- Collaborate with Forward Deployed PMs, core product, and design to turn customer needs into working solutions, often building a prototype before the meeting ends
- Lead technical demos, document implementation decisions, and maintain architecture diagrams that actually reflect reality
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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