Director of Engineering, AI Agents

About This RoleAI processing…

Key Responsibilities

• 1
  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.
• 2
  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.
• 3
  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.
• 4
  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.
• 5
  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.
• 6
  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).

Requirements

• 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.
• About you 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.
• What we’ll offer Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission.
• The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process.

Perks & Benefits