Director of Engineering, AI Platform

Asana Asana · Enterprise · San Francisco, CA · Product Engineering

Director of Engineering to lead an AI Platform organization responsible for foundational systems powering AI experiences. This includes teams focused on context (search, retrieval, knowledge extraction), LLM foundations (model serving, inference, provider strategy, evaluation), and AI efficiency (cost, quality, performance). The role drives strategy, execution, and architecture for agentic enterprise software, aiming for a reliable, economical, and performant platform.

What you'd actually do

  1. Lead the multi-year vision and technical strategy for Asana’s AI platform, covering retrieval and agent context, model serving and inference, model portfolio strategy, and evaluation systems.
  2. Own cost-per-execution as a primary engineering metric, managing model selection, routing, open-weight versus frontier trade-offs, inference optimization, caching, and prompt efficiency to protect product margins at scale.
  3. Establish evaluation frameworks, regression prevention, and performance standards that product teams can rely on out of the box, making quality, cost, and latency measurable defaults.
  4. Lead and mentor managers and their teams across San Francisco and New York City, building autonomous owners, recruiting top talent, and maintaining high execution standards.
  5. Evaluate when to adopt frontier models versus open-weight models and structure provider relationships to prevent vendor lock-in.

Skills

Required

  • Engineering leadership
  • Managing engineering managers
  • AI platform strategy
  • Model serving
  • Inference infrastructure
  • Cost optimization
  • Evaluation systems
  • Agentic frameworks
  • RAG architectures
  • Distributed team leadership
  • Technical strategy
  • Architecture

Nice to have

  • Provider strategy
  • Knowledge extraction
  • Prompt efficiency
  • Open-weight models
  • Frontier models
  • Vendor lock-in prevention
  • Build-versus-buy analysis
  • Cross-functional partnerships

What the JD emphasized

  • lead four key teams through their engineering managers
  • end-to-end strategy, execution, and architecture
  • make Asana’s AI platform the most reliable, economical, and performant foundation in the industry for agentic enterprise software
  • giving Asana the leverage to ship AI products faster than anyone else
  • 12+ years of software engineering experience with 5+ years of engineering leadership, including 2+ years managing engineering managers
  • Proven track record of using AI tools daily, with deep expertise in serving architectures, inference providers, agentic frameworks, RAG architectures, and scale evaluation systems.
  • Proven experience optimizing infrastructure costs and unit economics at scale with concrete metrics and clear trade-offs.
  • Platform mindset centered on earning trust, establishing clear standards, providing responsive support, and using data to guide team priorities.

Other signals

  • AI Platform
  • model serving
  • inference infrastructure
  • cost optimization
  • evaluation systems
  • agentic enterprise software