AI Catalyst
We are looking for an AI Catalyst to unify AI across Muse and turn it into a scalable execution engine that compounds impact from idea to delivery to iteration. We are becoming an AI-first company where AI is not a feature, but the default way work gets done across product, engineering, and operations.
Key responsibilities
- Own the Muse AI-first roadmap end-to-end: Horizontal AI engineering ownership — single accountable lead for all AI engineers at Muse.
- Product AI: partner with product and engineering leadership to ship AI features on priority product surfaces. Define the product-AI roadmap and the metrics that prove user value, retention and monetization.
- Operating AI: work with function leaders to launch AI-first workflows in 7–9 pilot non-tech functions.
- AI architecture ownership: model/provider selection, agent design, RAG vs fine-tuning, evals, AI infrastructure decisions for Muse.
- Engineering AI: drive full-chain AI across how Muse builds software: code review, testing, documentation, deploy, incident response, codebase intelligence, release velocity.
- Define standards, evals and the shared platform so all teams can build AI safely.
- Visible internal driver of AI-first culture — adoption through systems, tooling, evidence and AI Champions.
Required experience
- Orchestrator DNA: taste, agency, judgment, systems thinking, fluency in what machines can vs cannot do, ability to decompose problems into Clear / Complicated / Complex / Chaotic and decide what's agent-led vs human-led.
- 5+ years of AI/ML-adjacent leadership inside a product company.
- Recent (last 1–2 years) hands-on experience with agentic-coding stacks: Claude Code / Cursor or equivalent, MCP, sub-agents, evals, custom commands, permission rules, per-repo context files.
