/roles — ROLE_480
AI Product Engineer / Forward Deployed Engineer
Fast-growing startup providing QA, red-teaming, and observability for enterprise voice AI agents
The role
- COMP
- $140K - $180K
- EQUITY
- Competitive equity
- LOCATION
- New York · San Francisco · South Bay Area · Los Angeles · Boston · Seattle · Texas · Chicago · Washington DC · Denver · Florida · Minnesota · Sacramento
- WORKPLACE
- Remote
- EXPERIENCE
- 0 - 3 years
- VISA
- None, Visa transfers
- STACK
- TypeScript, Python, React, Next.js, NodeJS, TailwindCSS, OpenAI, AWS, Kubernetes, K8s, PostgreSQL, Redis, Terraform, Figma
- INDUSTRY
- AI, B2B, Devtools, Enterprise
The company
Early-stage company automating testing, red-teaming, and production monitoring for voice AI agents, using simulated callers to find bugs before and after launch.
- STAGE
- seed-stage
- FUNDING
- seed funding
- TEAM
- ~15 people
- FOUNDED
- 2024
- BACKING
- VC-backed
JD — the work
About the role
You would build and ship features yourself, partnering closely with enterprise clients to turn what they need into product. The company is a small, senior-heavy, accelerator-backed team that was early to define QA for voice agents, deploys several times a day, and is moving into very large enterprise accounts. Its platform covers simulating many calls before release, adversarial red-teaming, and observability on live calls, with customers in regulated industries such as healthcare, financial services, and telecom.
What you'll do
- Work daily with customer engineers who build voice agents, identify what is missing, and build the fix yourself
- Take features from discovery to prototype to release, working on both front end and back end
- Help enterprise accounts through pilots and after the sale as a technical partner who gets things done
- Solve customer problems quickly, then generalize the fixes into reusable platform features
- Lean on AI coding assistants every day to move fast
What they're looking for
- 0 to 3 years of engineering experience
- An AI-native workflow: daily use of AI coding assistants that you can demonstrate concretely
- Good product and design judgment: able to turn a fuzzy request into a clear feature with no formal spec
- Ease working with technical customers, engineers as well as PMs
- Proficient with Python and TypeScript, writing and owning production code yourself
- A degree from a highly selective university (a firm requirement)