Director, Engineering (Patient)

About Headway

Headway's mission is to build a new mental health care system that everyone can access. We've built technology that takes the hardest parts of mental healthcare—finding the right provider, navigating insurance, managing payments—and makes them simple. We're now one of the fastest-growing companies in healthcare, with more than 200,000 patients finding care through Headway and thousands of therapists using our platform to grow their practices.

Principles That Guide Us

• Matching quality is the foundation of therapeutic outcomes— we obsess over getting patients to the right provider
• AI is how we get there— from ML-powered ranking to LLM-assisted patient experiences to AI-augmented engineering workflows
• We ship fast and learn fast, but patient trust comes first— especially when AI is influencing decisions about someone's mental healthcare
• We build for the whole marketplace: patients, providers, and payers
• Explainability matters— in healthcare, "the model said so" isn't enough

The Problems You'll Solve

• Build the AI-powered matching engine that defines Headway's next chapter
• Ship AI product features that make the patient journey feel intelligent
• Define what AI-era engineering looks like for your teams
• Close the gap between engineering output and patient outcomes
• Evolve team structure as the product evolves

Key Responsibilities

• Set AI and engineering strategy for the core patient experience in partnership with Product and Data Science leadership
• Lead 3 Engineering Managers; scale the org from ~18 to ~30+ engineers over the next 18 months
• Co-own patient funnel metrics with your Product and Data counterparts— not just deliver against them
• Ship ML-powered matching, reimagined patient onboarding, and patient activation systems
• Own the AI product roadmap for your pods: where we use ML, where we use LLMs, how we reason about explainability and patient safety
• Establish the operating model where engineering, product, and data science jointly own these metrics— a true triad, not one where engineering is an execution arm
• Evolve team structure as the product evolves

Required What You Bring

• 10+ years of software engineering experience, 5+ years managing engineering managers
• Led engineering for a consumer or marketplace product where search, matching, ranking, or personalization was core to the business
• Shipped ML-powered product features at consumer scale and can make sound architecture calls on how they get built
• A practiced, opinionated perspective on AI-augmented engineering workflows— you've led teams through adoption and have concrete views on what changes in code review, testing, hiring, and engineering culture
• Track record of moving business metrics (conversion, retention, engagement) through engineering-product partnership, not just delivering features on time
• Technically credible enough to engage deeply on ML systems, marketplace infrastructure, and consumer-facing architecture— you don't write code daily, but you can spot the problems in a design review
• Comfort working in a regulated environment where you must reason about bias, explainability, and patient safety in ML systems
• Strongly Preferred: Experience building LLM-based product features (conversational interfaces, intelligent triage, AI-assisted workflows)— this is where patient-facing AI is heading and we want someone who has been there
• Experience rethinking team structure or hiring profiles in response to AI productivity gains— you've thought through what a high-performing team looks like when AI is a meaningful part of how code gets written
• Experience with marketplace dynamics (supply/demand balancing, multi-sided incentive design)