What are the responsibilities and job description for the Applied AI Engineer position at wordware (YC S24)?
⚠️ Please read first
As an Applied AI Engineer , you’ll be responsible for building, refining, and scaling the agent systems inside Wordware — from architecture to evals to deployment.
This isn’t a research role. We care about what works in production: fast response times, predictable behavior, traceability, and uptime.
You’ll work across the stack — with infra, frontend, and product — to make sure the agents users build inside Wordware are robust, useful, and usable.
A Few Examples Of What You Might Work On
Minimum
We keep our process simple. Exceptional candidates go from first touch to offer within 2 weeks.
- This is a full-time, in-person role based in San Francisco (Presidio) - we work from the office 5 days a week.
- You must be based in the Bay Area or willing to relocate before starting.
- We require US work authorisation , but are open to O-1 visa sponsorship for truly exceptional candidates.
As an Applied AI Engineer , you’ll be responsible for building, refining, and scaling the agent systems inside Wordware — from architecture to evals to deployment.
This isn’t a research role. We care about what works in production: fast response times, predictable behavior, traceability, and uptime.
You’ll work across the stack — with infra, frontend, and product — to make sure the agents users build inside Wordware are robust, useful, and usable.
A Few Examples Of What You Might Work On
- Implement multi-step, tool-using agents that hit real APIs and handle retries, auth, timeouts, and edge cases.
- Build RAG pipelines that support grounded answers from structured and unstructured sources.
- Design agent memory systems that persist relevant state across runs — e.g. scratchpads, summary buffers, embedding stores.
- Add determinism replay to agents so users can trace and debug behaviors step by step.
- Own and evolve our eval framework — both automated checks and human-in-the-loop scoring.
- ${your ideas}.
Minimum
- 3 years of engineering experience , including time shipping production software.
- You've built and deployed agent-like systems — multi-step LLM pipelines, tool-using bots, scripted assistants, or similar.
- Hands-on experience with:
- You write production-grade code and can work across systems without needing a spec.
- You thrive in fast-paced, product-first environments where the goal is shipping.
- Experience with frameworks like LangChain , CrewAI , or DSPy — or strong opinions about why you don’t use them.
- Shipped agents that are live in the wild — used by customers, not just internal demos.
- Familiarity with LLM ops , tracing, observability, and failure handling.
- You’ve been a founder or early engineer and care deeply about product quality.
We keep our process simple. Exceptional candidates go from first touch to offer within 2 weeks.
- Application
- 15-min intro call
- 45-minute technical interview
- System design interview
- Final conversation
- Work trial