Privacy Program Engineer
US$166,000 – US$175,000 / yr base salary
Posted 8 Oct 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 4–7 yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
| Base salary | US$166,000 – US$175,000 / yr |
|---|
About Us:
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
About the role
We're looking for a Privacy Program Engineer to own the technical core of our privacy program. We've achieved ISO 27001, ISO 27701, ISO 42001, and SOC 2 Type II, and we run active GDPR and CCPA/CPRA programs - now we need someone to run the machinery that keeps all of it working, and to make that machinery largely run itself.
This is a privacy role with real technical depth - you'll write scripts, queries, and automation. From day one you'll own real workstreams: data subject requests, the data inventory and ROPA, hands-on privacy reviews for new vendors and features.. You'll report to our Privacy Lead and be a key owner of large portions of our privacy program, as well as the key technical expert on the privacy team.
This is not a ticket queue with a title. We're a small team at a company that builds AI infrastructure, and we intend to leverage it - you'll own the direction and design of the technical systems, automations, and tools that help us meet our privacy obligations at Fireworks.
Who this role is for
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You build systems, not queues. You've used AI tooling, automation, scripting, or workflow platforms to eliminate manual privacy work.
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You're technical enough to be dangerous. You read code to understand what a service actually does with data. You can query a database without asking for help. You've automated something real with code, a workflow engine, or an LLM-based agent and you know how to build scalable tools running against production systems and data.
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You take a project and run with it. Given a rough problem and a deadline, you come back with it done. You’re not afraid to make tactical decisions and judgement calls.
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You take extreme ownership. You're comfortable owning something outright and figuring it out - your workstreams are yours. You surface problems early, fix them, and make sure they don't recur.