Senior Python Engineer

We are looking for

The Open Home Foundation is seeking a passionate Senior Python developer, based in Europe, to join our Home Assistant department as a full-time Software Engineer. This team is responsible for the open development, maintenance, and enhancement of the Home Assistant platform; supporting new functionality aligned with our roadmap and enabling the wider community to contribute and innovate easily.

Home Assistant is a highly popular open-source project, the largest open source project on GitHub by the number of contributors we have each year. As a result, we also receive many open-source contributions. In this role, you will work closely with the open-source community to review contributions and ensure seamless integration into our platform.

In this role, your main daily tasks will involve bringing Home Assistant to the next level of AI capabilities. You will help build the foundation on which AI features across our platform are created: the APIs and interfaces that let language models work with the home, Assist - our assistant that people talk to or chat with, in-product agents, and the open standards (such as the Model Context Protocol) that connect Home Assistant to the wider agentic world. Always private, local-first, and by choice. This is not a list of features to deliver, but a long-term direction to help shape: AI is becoming part of how people use and manage their homes, and Home Assistant will lead that in the open. You will ensure the successful integration of features that align with our mission to build a more private, open, and sustainable smart home ecosystem.

A note on the job title: at its heart, this is an AI engineering role, and we deliberately didn't put that in the title. Home Assistant runs in millions of homes, and AI features need to be engineered with the same rigor as everything else in our core. We are looking for a strong Python engineer who has built and shipped serious LLM-powered software, not someone whose experience stops at writing prompts.

What you are going to do

• Design and build the AI foundation of Home Assistant: the conversation APIs, LLM integrations, and the typed tool layers that every AI feature in our platform builds upon.

• Create in-product agents that help people build and manage their homes together with AI, grounded in their home's actual configuration, and always with the user in control: the assistant proposes, the user approves.

• Connect Home Assistant to the agentic world through open standards like MCP, so external AI systems can work with and build on the home, safely, with properly scoped permissions, and always under the user's control.

• Grow Assist from home control into home management: make our assistant context-aware, give it memory across sessions, and teach it to help with documentation, configuration, and diagnosing problems, whether people speak to their home or type to it. All of it with the choice between local and cloud models.

• Make AI features easy to discover, set up, and disable: AI in Home Assistant is powerful, optional, and always under the user's control.

• Build AI-powered workflows that help us and our community manage and structure the largest open source project on GitHub: think issue triage, review assistance, and contributor tooling.

• Conduct code reviews of pull requests from your teammates and our community, identify and resolve technical issues, ensuring we maintain high coding standards.

• Collaborate with our community to investigate and address reported issues.

• Provide input and help with deciding on architectural proposals and changes to our code base.

What you need to have

• 5+ years of experience working in Python back-end development.

• 3+ years of experience working with asyncio and threading.

• Built and shipped LLM-powered features in production Python: tool calling, agent loops, streaming, evaluation, and handling the many ways models fail. Using AI coding assistants or prompting alone does not qualify.

• Experience building with the Model Context Protocol: you have designed and implemented MCP servers or clients, or comparable tool-calling interfaces for agents.

• Experience with local, on-device inference (e.g., Ollama, llama.cpp).

• A pragmatic view on AI: you know what language models are great at, where they fall flat, and how to design systems that stay reliable, private, and safe regardless.

• Strong problem-solving abili