Product Engineer

Title: Product Engineer Location: San Francisco, CA, US / Remote (DE; New York, NY, US; Toronto, ON, CA; Toronto, Ontario, CA) **About Us** Asendia AI is rebuilding how the world hires. The global staffing industry is $600B+ and still runs on manual phone calls and gut feelings. We built AI agents that screen, interview, and score candidates 24/7, live, in real time, at a fraction of the cost. We work alongside staffing agencies across the US and Europe who expect speed, accuracy, and scale, and we hold ourselves to the same bar. Already running thousands of AI-powered screens, our agents place candidates within days of going live and cut screening costs by 90%. YC-backed. Seed-stage with years of runway. AI penetration in staffing is still under 1%, and there's no dominant platform yet. We're building it, AI-native from day one. Joining Asendia means three things: * **We lean in:** ownership over titles, outcomes over intentions. * **We fight for excellence:** high standards, direct, ego-free feedback. * **We build with AI:** the best tools, in the product, and in how we ship. Mission before ego. Everyone contributes. No one coasts. If you're driven by impact, pace, and raising the bar, this is the place. **The role** As a Product Engineer at Asendia, you'll build the AI agents that _are_ the product, the voice interviewers that talk to thousands of candidates, and the systems that turn those conversations into decisions. You'll work across the stack with real ownership and autonomy, and see your work hit real users the same week you ship it. What you'll be doing: * Design and ship voice AI agents: real-time phone interviews with sub-300ms latency (LLM orchestration, WebSockets, FastAPI) * Build the prompt and agent architecture: reusable, multi-vertical interviewer systems, each client customizes their own screening logic, voice personality, compliance rules * Turn messy voice conversations into structured, reliable candidate scores * Run evals and reliability work: audit agents across a live fleet, catch regressions, keep behavior consistent at scale * Build the agentic infrastructure that lets every client spin up and tune their own screening workflows **Who you are** * A passionate engineer who's shipped AI agents end-to-end, not demos, things real users hit * Fluent with LLMs, prompting, and agent orchestration; you know where models break and how to engineer around it * You build _with_ AI tools, not around them. Agentic coding is part of how you ship * Strong in Python and comfortable across the stack; you don't wait on anyone to finish a feature * High-agency: no docs, no playbook, a client deadline on Friday—you figure it out * You think about the product, not just code—you understand why a screening flow matters to a recruiter and build accordingly Bonus: voice/speech systems, real-time streaming, eval frameworks, or prior staffing/recruitment experience.