The opportunity
AI Teammates are Asana’s flagship AI innovation - autonomous agents embedded directly into enterprise workflows that reason, act, and proactively drive work forward. The AI Teammates Platform (AITP) team owns the execution engine and platform layer that makes these AI Teammates effective, reliable, and scalable.
What you'll do
Set the technical strategy for the AI Teammates execution engine, tool: orchestration, and platform APIs within Asana, advocating for engineering-driven investments with a vision for keeping our systems flexible, reliable, and maintainable to meet customer needs now and in the future
Drive the team to continually and holistically better itself, setting high: standards for clean architecture, systems reliability, and evaluation methodologies while enabling the engineers around you to deliver at high velocity and grow their skills
Be a key collaborator with other groups across Engineering and a technical: counterpart to the AI Teammates team’s Engineering Manager, serving as a partner to external model providers (OpenAI, Anthropic) and representing our platform capabilities across team boundaries
Partner with Product Management, Design, Data Science, and User Research to: deeply understand agentic work patterns, and propose elegant solutions to make AI Teammates effective and trustworthy
Architect and own the composable platform foundation, partnering with product: engineering teams to enable them to build agentic capabilities into their domains in a self-serve manner
Oversee the execution of high-impact technical initiatives—from advanced: proactivity and MCP integrations to model evals, latency tuning, and cost optimization—ensuring our systems scale safely with frontier LLM updates
What they're looking for
- + years of software engineering experience working in large codebases, with: strong backend, systems, or reliability fundamentals.
- + years leading engineering teams or serving as a technical lead, with a: track record of driving technical strategy, timeline planning, and risk mitigation.
- Experience or deep interest in Applied AI / Agentic Systems: Familiarity with agent orchestration, tool integration, model evaluation frameworks, RAG, or production LLM observability.
- Quick learner and comfortable transitioning between different contexts and: codebases, enabling you to jump in and rapidly unblock teammates facing thorny obstacles
