The opportunity
We’re looking for an experienced engineering leader to lead and scale Asana’s flagship AI Teammates Pillar within our Core/AI Organization. Reporting directly to the Head of Engineering, AI & AWM, you will oversee an engineering area encompassing four key teams: AI Teammates…
What you'll do
Drive Strategy & Execution Across the AI Teammates Pillar: Lead, set direction, and align goals/metrics across four core engineering teams (Platform, Experience, Chat, and Agent Orchestration) to execute on Asana’s flagship AI vision while balancing business, customer, and technical needs.
Architect Enterprise-Grade AI Platforms & Systems: Own the end-to-end technical strategy across model rollouts, eval infrastructure, tool orchestration, Model Context Protocol (MCP), and proactivity engines—enabling Asana to operate reliable agentic systems for top-tier enterprise customers.
Define Next-Generation Human-AI Collaboration: Lead product and platform engineering teams delivering full-screen and docked chat surfaces, discovery/onboarding flows, in-product explainability, human-in-the-loop workflows, and ROI/governance experiences for administrators.
Pioneer Multi-System Agent Orchestration: Build integrations, Agent Skills, and MCP frameworks that allow AI Teammates to act as the central control point for complex, multi-step workflows across external tools like Slack, Salesforce, coding agents, and internal systems.
Scale Engineering Leadership & Culture: Plan and implement the scaling of your engineering organization. Recruit, close, and retain top engineering talent and managers, develop leadership capabilities across teams, and foster an inclusive environment centered on engineering excellence and psychological safety.
Bridge Cross-Functional & External Strategic Alignment: Align technical, product, and business perspectives across R&D, Product, Design, Security, and Legal, while maintaining close strategic partnerships with frontier AI labs (e.g., OpenAI, Anthropic).
What they're looking for
- Proven Leadership Experience: 8+ years of software engineering experience with 4+ years leading multiple engineering teams or managers, with a track record of driving multi-team strategy and delivering complex production systems.
- AI & Agentic Systems Expertise: Deep understanding of applied AI, LLM evaluation frameworks, agent/tool orchestration, Model Context Protocol (MCP), proactivity models, and production observability.
- Systems & Product Engineering Mastery: Experience spanning backend/systems reliability, complex full-stack product interfaces, and enterprise governance/permissions models operating at scale.
- Strategic Trade-off & Risk Management: Proven ability to balance short-term customer deliverables with long-term architectural investments and navigate ambiguity over multiple quarters.
