About the job
Rhythms develops AI technologies that help organizations operate with greater autonomy. The founding team previously built Ally.io, acquired by Microsoft, and the company is supported by investors such as GreenOaks, Madrona, and Accel. Rhythms has earned recognition from GeekWire and is listed among the top AI innovators for 2025. Its platform is already used by Fortune 100 firms, healthcare systems, and logistics organizations worldwide.
The core platform uses a multi-agent AI architecture to automate business processes, monitor progress across systems, identify risks early, and reduce manual work. Integrations with Slack, Teams, Jira, and Linear help keep operations connected and efficient.
Role overview
This AI Product Engineer role is based in San Francisco and offers broad responsibility across multi-agent systems, large language model (LLM) orchestration, and the customer-facing product. The work is hands-on, with daily feature releases to production, direct customer interaction, and rapid feedback cycles. The position involves identifying problems, designing and implementing solutions, and taking ownership of the results.
What you will do
- Develop agent systems that autonomously manage business operations, including OKR execution, MBR/WBR cadences, and Auto-Pilot workflows, with a focus on enterprise reliability.
- Oversee features from discovery and design through implementation and measurement.
- Design multi-agent systems that balance performance and reliability, making informed decisions on models, orchestration, and evaluation methods.
- Create chat-native product experiences that blend strong product sense with thoughtful systems design.
- Advance the AI stack by using tools such as Claude Code and Cursor, shipping new AI features weekly, and adapting as models evolve.
Requirements
- 2–5 years of experience building production software, with hands-on work involving LLMs, agents, or AI-native products beyond prototypes or demos.
- Strong Python skills and familiarity with React/Next.js, along with experience in distributed systems.
- Customer-focused approach, prioritizing user impact over technical architecture alone.
- Track record of delivering agent systems that perform reliably in production settings.

