Member of Technical Staff
Fireworks AI
Member of Technical Staff
Fireworks AI
AI inference platform for model deployment
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.
Every developer who tries Fireworks has a first five minutes. They land on the site, sign up, grab an API key, pick a model, and make their first call. If it works, they build. If it fails, they leave, usually for good.
Developer Experience drives that journey and everything after it: the path from first visit, to first successful API call, to a team running production workloads and growing on Fireworks across inference, fine-tuning, and the rest of the platform.
We're looking for a product-minded engineer to join as one of the first engineers on Developer Experience, and own the surfaces that make that path real: signup and onboarding, the developer console, quickstarts, the API and model playground, model choice and defaults, error messages, pricing, billing and usage, and lifecycle messaging.
You'll work directly with external customers, from solo developers to enterprise engineering teams. You'll get on calls, watch them build, and turn what you learn into products that customers and developers actually use. You'll also look across the whole platform, from inference and fine-tuning to the console and billing, for the places where a new 0-to-1 product can unblock users and drive exponential growth.
This is a high-autonomy IC role on a small team. There's an early roadmap, but the market moves every week, so you'll help find the problems as much as solve them. You'll own features end to end: from watching where developers get stuck, to designing the fix, to shipping it, to seeing whether it worked. If you're the kind of engineer who ships fast, cares how a product feels, and doesn't wait to be told what to build, this role has enormous leverage and nothing standing between you and impact.
Own product surfaces end to end across the developer journey: signup, onboarding, the developer console, quickstarts, the API and model playground, model selection, errors, pricing, billing, and usage. Scope the problem, build it, ship it, instrument it, and iterate on real usage.
Cut time to first working request: useful errors, smart default models, quickstarts and SDK paths that work the first time, and a reason to come back.
Work directly with external customers: join calls, embed with their teams, and be the engineer they talk to when something is hard. Build products that customers and developers actually use, not just ones that look good on a roadmap.
Look across the platform and every part of Fireworks for 0-to-1 opportunities: places where a new product, tool, or workflow would unblock users and drive exponential growth. Prototype it, prove it with real customers, and scale it.
Make Fireworks easy to drop into the tools developers already use, through our OpenAI-compatible APIs, SDKs, CLIs, and AI coding tools, so getting started is a base URL and a model ID.
Work across the full stack: frontend (React/TypeScript), backend services (Python, Go), APIs, and data layers, to ship polished, fast, production-quality product surfaces for deeply technical users.
Build the foundations the team doesn't have yet: event tracking, funnels, an experimentation framework, and lifecycle messaging, so the whole company can test ideas and learn fast.
Talk to developers directly. Watch them build, see where the first call fails, and bring that back as working code.
Build for a platform that changes week to week: new models, new products to onboard into, new pricing and consumption models, and new ways developers build with AI.
Partner closely with Product, Design, Growth, Marketing, Data, Infrastructure, and Sales so self-serve works alongside our sales-led motion.
Instrument everything you build and let the data tell you where the friction is, then remove it.
5+ years as a software engineer, with meaningful time spent building and shipping user-facing products.
Strong full-stack skills, comfortable across frontend (React/TypeScript), backend (Python, Go, or similar), APIs, databases, and SQL.
A track record of shipping developer-facing products: APIs, SDKs, consoles, dashboards, CLIs, or developer tools.
Experience working directly with external customers and turning what they tell you into product.
You've built 0-to-1 products: taken an idea from nothing to something people use and grow with.
Genuine end-to-end ownership: you're as comfortable scoping an ambiguous problem as you are deploying the fix at 2am.
Strong product instincts and a designer's eye: you care about interaction details, copy, and how a flow feels, and you can make a technical product feel simple.
Hands-on with product analytics: you instrument what you ship and use the data to decide what to build next.
The ability to operate at high velocity with extreme ownership: you ship in days, make pragmatic trade-offs, and don't wait to be told what to build.
Clear written and verbal communication with engineers and non-engineers.
A Bachelor's or Master's degree in CS, EE, or equivalent experience.
Experience owning onboarding, activation, growth, or monetization surfaces at a developer-tools, API, or infrastructure company.
Experience building products on top of complex infrastructure, inference platforms, cloud services, data platforms, or ML tooling.
Experience designing and reading A/B tests and funnel experiments with rigor.
Experience with usage-based pricing and billing, or with self-serve inside a company that also sells top-down.
Comfort in a fast-moving, founder-led environment where the product changes week to week and you're drawing the map as you walk it.
You build with AI tools and LLM APIs every day, and have sharp opinions on what great onboarding for an AI developer platform feels like.
A portfolio, side projects, or launches that show your taste and range. Non-traditional paths welcome.
We'll look closely at work you personally identified, built, and shipped, and what you learned after launch. Come ready to walk us through a developer-facing product you owned end to end, and a time you saw a problem no one owned and drove it to a measurable outcome. Expect a practical product and engineering exercise, not pure algorithm puzzles.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.
AI inference platform for model deployment
Fireworks AI provides an AI inference platform that helps organizations run, customize, and deploy machine learning models. It supports deployment, fine-tuning, and inference workflows, with access to open-source models and on-demand deployment options through a subscription model. The platform enables users to configure and optimize models for production environments, manage variants, and scale AI workloads while controlling costs. Unlike some competitors, the emphasis is on end-to-end production-grade inference and fine-tuning across a range of clients, from tech firms to research institutions and enterprises, with tools tailored for rapid deployment and cost efficiency. The long-term goal is to expand the use of AI in production by building compound AI systems, growing the team, and delivering broader platform capabilities that accelerate AI adoption in real-world settings.
Explore more opportunities at Fireworks AI