Product engineer at Fireworks AI building developer-facing surfaces for an inference platform. Work across frontend, backend, and APIs to ship features for the console, fine-tuning workflows, billing, and agentic tooling.
We're looking for a product-minded engineer to join Fireworks as a Member of Technical Staff on our Product Engineering team. You'll build the product surfaces that developers and enterprises interact with every day — from the inference API and developer console to fine-tuning workflows, model deployment, billing, and new products like Fire Pass.
Fireworks owns the full stack: training, fine-tuning (SFT and RFT at frontier scale), serverless and dedicated inference, multi-LoRA serving, and agentic orchestration — all on infrastructure we built from scratch. Product Engineering sits on top of that stack and turns it into things developers and Enterprises can actually use. You'll work across the surfaces where our platform meets its users: the APIs they call, the console they configure deployments in, the fine-tuning jobs they launch, the billing systems that meter their usage, and the agentic tooling they build with.
This is a high-autonomy IC role. You'll own features end-to-end — from understanding the problem, to designing the solution, to shipping it, to watching how developers actually use it. We're a small team building a platform that processes trillions of tokens daily, so the work you do will be used immediately and at enormous scale.
Design, build, and ship product features across the Fireworks platform — including the developer console, API surfaces, model playground, fine-tuning workflows, deployment management, and billing
Own features end-to-end: scope the problem, build the solution, ship it, instrument it, and iterate based on real usage
Build and improve the developer experience for Fireworks' core product capabilities — serverless and on-demand inference, supervised and reinforcement fine-tuning, multi-LoRA serving, and agentic orchestration
Work across the full stack — frontend (React/TypeScript), backend services (Python, Go), APIs, and data layers — to deliver polished, production-quality product surfaces
Build for products that are evolving rapidly: new model types, new serving paths (standard, priority, fast), new consumption models like Fire Pass, and new capabilities like multi-agent harness tooling
Partner closely with Infrastructure, Applied Research, Growth, Data and Design to translate platform capabilities into intuitive developer-facing products
Instrument and monitor the systems you build, using data to understand how developers use the platform and where friction exists
Move fast and make pragmatic trade-offs — the pace of AI infrastructure demands shipping early, learning quickly, and iterating with conviction
3 years of experience as a software engineer, with meaningful time spent building user-facing products
Strong full stack development skills — comfortable working across frontend (React/TypeScript), backend (Python, Go, or similar), APIs, and databases
Experience building and shipping developer-facing products: APIs, dashboards, consoles, CLIs, or developer tools
Track record of owning features end-to-end — you're as comfortable scoping a problem as you are deploying the fix
Strong product instincts — you think about the developer experience, not just the implementation
Demonstrated ability to operate at high velocity with extreme ownership: you ship fast, make pragmatic trade-offs, and don't wait to be told what to build
Experience building products on top of complex infrastructure — inference platforms, cloud services, data platforms, or ML tooling
Experience building for deeply technical users (developers, ML engineers, platform teams) where the product surface is an API as much as a UI
Comfort working in a fast-moving, founder-led environment where the product is evolving week to week and the map is being drawn as you go
You build with AI tools daily — you use them to accelerate your own work and have strong intuition for what great AI developer experience looks like from the inside