Senior Backend Engineer, AI / LLM

We are hiring a Senior Backend & AI Engineer who pairs strong Python backend engineering with real, hands-on AI experience building LLM-powered products.

This is not a traditional backend role with AI bolted on. We want an AI-native engineer who already lives in the ecosystem: someone who follows new models, ships with them, and stays plugged into technical communities on X and GitHub.

WHO THIS ROLE IS FOR

You are a Senior Backend Engineer with 5+ years of experience, deep Python skills, and genuine curiosity about how systems work under the hood. You have built production AI features with LLMs, agents, RAG, and vector databases, and you can own a feature end to end from architecture to deployment.

WHAT YOU'LL DO

• Design, build, and scale backend systems, APIs, services, and integrations in Python
• Ship production AI features using LLMs, agents, RAG, vector databases, inference, and tool calling
• Own features end to end, from architecture through deployment and iteration
• Evaluate and implement emerging AI models, inference platforms, and developer tooling
• Debug, optimize, and improve system performance, scalability, and reliability
• Use AI coding tools daily to move faster without dropping quality

WHAT WE'RE LOOKING FOR

• 5+ years of software engineering experience
• Strong Python backend engineering skills
• Solid Computer Science or Computer Engineering fundamentals
• Hands-on experience with AI, LLMs, and modern AI infrastructure
• C or C++ and low-level systems experience is a major plus
• Working knowledge of distributed systems, concurrency, networking, or operating systems
• Track record building production APIs, databases, integrations, and scalable systems
• Strong ownership and the ability to move fast independently
• Startup or high-growth experience preferred

THE AI-NATIVE MINDSET

You already know what is happening across models, inference, AI infrastructure, agents, and developer tooling. Platforms and models like Fireworks AI, Baseten, and GLM / Zhipu are familiar territory, and you follow their evolution through X, GitHub, research, and technical communities.

Strong signals we love to see:

• AI personal projects or GitHub repositories
• Open-source contributions
• Active experimentation with the latest models and AI tools
• A real technical presence on X or GitHub
• Curiosity about how things work under the hood
• The ability to evaluate new AI technologies on your own