Director of Engineering, AI Platform

Asana•San Francisco, CA

1d•Hybrid

About The Position

We are looking for a Director of Engineering to lead our AI Platform organization. This group builds the foundational systems powering every AI experience across Asana. In this role, you will lead four key teams through their engineering managers: Context (search, retrieval, and knowledge extraction across the Asana Work Graph), LLM Foundations (model serving, inference infrastructure, provider strategy, and evaluation systems), and AI Efficiency (our center of excellence for cost, quality, and performance standards across all AI workloads). Collaborating with engineering managers and senior technical leaders, you will drive the end-to-end strategy, execution, and architecture that define how humans and AI work together at Asana to build trusted, reliable, high-value product workflows for enterprise customers worldwide. Your mission is to 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. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

Requirements

12+ years of software engineering experience with 5+ years of engineering leadership, including 2+ years managing engineering managers.
You've built organizations, not just teams: you've hired and developed managers, restructured when the mission changed, and held a bar for both.
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.
Skilled asynchronous communicator with experience leading distributed teams across time zones using strategy docs and decision memos.
Adaptable decision-maker who takes clear, evidence-based positions but pivots quickly as new data emerges.

Responsibilities

Drive Strategy & Execution Across the AI Teammates Pillar: 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.
Optimize AI Infrastructure Costs: 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.
Establish AI Evaluation Frameworks: 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.
Lead and Mentor Teams: 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.
Manage Model Strategy: Evaluate when to adopt frontier models versus open-weight models and structure provider relationships to prevent vendor lock-in.
Architectural Leadership: Pressure-test architectural decisions, arbitrate build-versus-buy debates with data, and act as the trusted technical authority for AI infrastructure accuracy across the company.
Drive Cross-Functional Partnerships: Partner cross-functionally with product, go-to-market, and finance leaders to tie platform investments directly to business performance, unit margins, and enterprise trust.