Head of Engineering, Core Product & Collaborative Work Management

Asana Asana · Enterprise · New York, NY · Product Engineering

Engineering leader to own and scale foundational experiences of Asana's Core product, reimagining the core experience through AI-native workflows. Responsible for building systems that enable seamless collaboration at scale, leveraging AI to reduce "work about work" and accelerate human productivity. Owns technical strategy for central work management features, optimizing architecture for LLM-powered features, real-time data processing, and predictive work patterns. Builds "AI-first" platform capabilities powering intelligent agents, automated status reporting, and smart resource allocation. Drives engineering excellence in AI implementation, establishing best practices for prompt engineering, model integration, and data privacy. Grows engineering leaders toward generative and agentic product architectures. Represents Asana’s intelligent CWM capabilities to strategic customers.

What you'd actually do

  1. Lead the Core Product/CWM engineering organization as we scale to support complex workflows, balancing powerful functionality with AI-driven simplicity that keeps the user experience effortless.
  2. Own the technical strategy for Asana’s central work management features (tasks, projects, portfolios), ensuring our architecture is optimized to support LLM-powered features, real-time data processing, and predictive work patterns.
  3. Partner with Product and Design to define the future of AI-assisted collaboration, evolving our platform from a system of record to a system of intelligence that proactively helps teams organize and prioritize.
  4. Build "AI-first" platform capabilities that allow other teams to leverage our core work graph, providing the robust APIs and data structures necessary to power intelligent agents, automated status reporting, and smart resource allocation.
  5. Drive engineering excellence in AI implementation, establishing best practices for prompt engineering, model integration, and data privacy within the core product lifecycle.

Skills

Required

  • 10+ years of engineering experience
  • 5+ years leading teams
  • shipping high-impact products
  • integrating AI/ML into user-facing applications
  • collaborative software
  • distributed systems
  • AI can optimize complex data relationships and work graphs
  • AI-native user-centric design
  • using Large Language Models (LLMs) to enhance user workflow
  • modern AI stack
  • integrating third-party models (OpenAI, Anthropic)
  • internal ML services
  • production environment
  • building with AI Tooling
  • communication skills
  • bridge the gap between deep technical AI infrastructure and tangible business value

Nice to have

  • experience in how AI can optimize complex data relationships and work graphs
  • familiarity with integrating third-party models (OpenAI, Anthropic) or internal ML services into a production environment
  • Hands on experience building with AI Tooling

What the JD emphasized

  • AI-native workflows
  • AI-assisted collaboration
  • AI-first platform capabilities
  • intelligent agents
  • generative and agentic product architectures
  • prompt engineering
  • model integration
  • data privacy
  • integrating third-party models
  • internal ML services
  • production environment
  • AI Tooling

Other signals

  • AI-native workflows
  • AI-assisted collaboration
  • AI-first platform capabilities
  • generative and agentic product architectures