Software Engineer, AI Capture

What You'll Achieve

• Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership).
• Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization).
• Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable.
• Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems.
• Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “we talk and things get done.”
• Deliver enterprise readiness: sharing/permissions, compliance, and scalability for our fastest-growing customers.

Skills You'll Need to Bring

• Strong full-stack engineering skills (frontend + backend) and excitement to own user-facing product end-to-end.
• Product-minded craftsmanship: you sweat details, iterate quickly, and use data and user feedback to guide decisions.
• Experience building and operating production systems (debugging, on-call/incident response, performance, and reliability).
• Ability to work across ambiguous problem spaces, align stakeholders, and drive execution with high ownership.
• You don’t need to be an AI expert, but you’re curious and willing to adopt AI tools to work smarter and deliver better results.

Nice to Haves

• Experience with LLM / applied AI product development (prompting, evals, model integrations, or quality measurement).
• Experience with media / realtime pipelines (audio, transcription, diarization, streaming, low-latency processing).
• Experience building for enterprise customers (permissions models, compliance, scale, and security).

Compensation (San Francisco): Estimated base salary range $272,000 - $320,000 per year (plus equity and benefits).