Intermediate/Senior Product Engineer

Role Description

We’re building a voice agent that calls people who are past due on bills, explains their situation, and negotiates a payment arrangement in real time, without a human on the line. It uses synthetic voice, behavioral science, and LLM-orchestrated decision logic to run conversations that actually work. That’s the product. It’s technical, ethically loaded, and genuinely hard to build well.

This role exists at the intersection of product and engineering, and it leans hard into both. You’ll own the full lifecycle of that product:

• Pre-sales conversations where you help a client understand what’s possible
• Discovery where you find the real job-to-be-done
• Implementation where you build and ship it

You’re not a PM who hands off to engineering. You’re not an engineer who gets handed a spec. You do both, and you’re accountable for whether the product finds its market.

You’ll lead a small delivery team, one to two junior and intermediate engineers, operating on a parallel track to the core platform. What you learn feeds back into the roadmap. What you ship is the conversational product.

The domain matters. You’re building AI that makes real-time decisions with real financial consequences inside compliance guardrails, with a person on the other end of the line. Candidates who have worked in regulated, high-stakes AI application domains will have a meaningful head start.

If you’ve survived a client integration that went sideways at 11pm and have opinions about when to throw out what the model generated, read on.

Qualifications

• LLM orchestration depth is the floor
• Voice AI and telephony familiarity
• Full-stack implementation capability
• Client-facing discovery skills
• Integration and event-driven architecture
• AI tooling philosophy
• Multi-tenant systems experience
• Cloud deployment literacy
• Agentic SDLC toolkit fluency

Requirements

• Minimum 3 years experience building SaaS products at scale
• B2B experience is an asset

Performance Expectations

• 90 days: First client implementation is in active development with a clear delivery plan and a client aligned on scope. You’re fluent in the agentic SDLC toolkit. You’ve led at least one discovery conversation independently and can articulate where the product fits and where it doesn’t for that client’s context.
• 12 months: Three to four clients live on the voice AI product. A repeatable delivery motion exists — not just in your head, but documented and transferable. You’re feeding clear PMF signal back into the core roadmap, and there’s a case for growing the team or doubling down on the product direction.

You’re probably not a fit if

• You need detailed tickets and a tech lead to make forward progress
• You’ve built “integrations” but couldn’t explain the failure mode at the API boundary
• You’ve “worked with LLMs” but haven’t built a production agentic pipeline
• You’ve never been in a client conversation and don’t want to be
• You treat AI-generated code as ground truth