Why This Role

We're a YC + SoftBank-backed team that has launched a new venture within HR Tech — and revenue has doubled every month since launch. We're building AI agents that operate autonomously in the real world, including over voice. This isn't a wrapper on top of an LLM The core product relies on multi-step agentic workflows, real-time voice AI, and intelligent matching systems that get smarter with every interaction. We're hiring the engineer who will own these systems end-to-end — architecture, shipping, and iteration — and who will help us scale from rapid traction to category leader.

What You'll Own

Design and ship agentic AI pipelines — multi-step, tool-using, self-correcting workflows that operate reliably at scale without human intervention
Build and iterate on real-time voice AI systems: low-latency speech pipelines, turn-taking logic, interruption handling, and voice-to-action flows
Own intelligent matching and discovery systems — the core AI that powers how we connect the right people at the right time
Make high-leverage architectural decisions: when to use RAG vs. fine-tuning, how to structure memory across agent sessions, how to instrument and debug non-deterministic systems
Be a genuine thought partner to the founders on product strategy — shape the roadmap, not just execute it
Set the engineering bar and build the culture as the team scales

About you

Engineering foundation

7+ years of experience, including 5+ years shipping Node.js and React in production
Startup-tested: you've worked at a Seed or Series A company, made hard tradeoffs under pressure, and know what it takes to move fast with limited resources
Owned infrastructure end-to-end — CI/CD pipelines in GitHub Actions, Docker deployments to container orchestration, static assets to S3, and AWS services including Lambda, ECS, CloudWatch, and RDS

AI systems builder

Has shipped agentic or voice AI products in production — you have real scars from debugging non-deterministic, latency-sensitive systems at scale
Deeply familiar with LLM failure modes: hallucination, context limits, tool-calling reliability — and knows how to build guardrails that actually hold
Fluent in AI tooling across the full development lifecycle, from architecture and planning through to scaling; strong prompt engineer who knows how to get reliable output from models

How you work

Product-minded: you think in user outcomes, not tickets, and you push back when the spec doesn't make sense
Highly autonomous — you identify what matters, prioritize ruthlessly, and execute without hand-holding
Wired for speed without sacrificing quality: you ship fast and ship things users love, and you know the difference between acceptable debt and the kind that kills momentum
Strong communicator — equally comfortable in a technical architecture discussion and a conversation with a non-technical client or stakeholder

Nice to Have

Experience with real-time audio streaming, voice AI, or telephony integrations (Twilio, Vapi, etc.)
Prior work on RAG pipelines, vector databases. or embedding-based retrieval systems
Bay Area based — not required, but a plus

The hard problems here are real: keeping agents on-task, making voice feel natural, building systems that work when the model surprises you. If that's the kind of engineering you want to spend your time on — and you want founding-level ownership doing it — let's talk.

SilkChart

Latest Jobs

Founding Engineer