Senior/Staff Product Engineer (AI Staffing Marketplace)
ScrumAID
San Francisco, CA · Posted November 1, 2026
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Where San Francisco, CA ranks
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November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
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- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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Pay compared with the market
This listing does not state pay. Across 181 open senior listings that state pay, the middle half runs $175,500 to $255,000 and the median is $215,000.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
AI use among mechanical engineers is little observed so far. Measured exposure for mechanical engineers: 8% (little observed).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
A venture-backed staffing marketplace is rebuilding its product around AI agents and is hiring senior and staff engineers to join the founding engineering group. There are two flavors of work: applying existing agents and frontier models across the product, or building the underlying agent platform. Either way, the engineer partners with the CTO on architecture and will shape how the company builds for years.
The work
Decide where agents fit throughout the product to automate sourcing, vetting, matching and placing workers
Architect and lead central systems, including live matching and self-running vetting pipelines built on ML and agents
Own the platform’s design with the company’s future needs in mind, and push backend speed, resilience and scale
On the agent side, design the orchestration runtime, the evaluation and observability tooling, and connections into customers’ own operational software
Make foundational choices on which models to use, how the harness is designed and how retrieval, memory and tools work, and treat measurement of quality as true engineering craft
Spend time on customer sites with the people running operations and turn what you observe into repeatable deployment patterns
About you
Five to ten years owning products end to end on early-stage engineering teams, roughly five-plus for senior and seven-plus for staff
Has built zero-to-one agentic AI products and taken agent systems live, including evals and on-call
Deep in Python or TypeScript and Node.js, with distributed systems, APIs and data models on PostgreSQL and message queues such as Kafka or RabbitMQ
Uses coding agents daily and can take an ambiguous problem to a working prototype quickly
Strong product intuition and a specific reason for wanting a staffing marketplace with operations-heavy customers
On-site in the San Francisco Bay Area or New York, NY. Visa transfers considered.