Director, Engineering - Patient

Headway•Seattle, WA

6h•$264,000 - $330,000

About The Position

1 in 4 people in the US have a treatable mental health condition, but most providers don't accept insurance, making therapy too expensive for most people. Headway’s mission is to fix this by building a new mental healthcare system everyone can access. We started by solving the biggest barrier to care: insurance. The admin work - credentialing, claims, payment reconciliation - is a nightmare. We've automated that. But we're going further. Over 70,000 providers across all 50 states run their practice on our software, serving over 1 million patients. We are building the best tools for therapists to run their entire practice, reimagining the experience of finding a therapist, and investing in the platform foundations to enable this at scale. We aren't just a billing layer; we are becoming the platform where care actually happens. We're a Series D company with $325M+ in funding (a16z, Accel, GV, etc.), looking for exceptional people to help us achieve this mission. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. 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. About Patient Core Experience at Headway The Patient Core Experience team owns how patients find the right therapist on Headway. From search through the first several sessions, our four engineering pods — Onboarding, Profiles + Checkout, Ranking + Relevance, and Activation — build the systems that make great therapeutic matches happen. We operate a three-sided marketplace (patients, providers, payers) with real complexity and massive impact. We're evolving from a provider directory into an intelligent matching platform that uses communication style, data-backed expertise signals, and patient-reported outcomes to connect people with therapists who are genuinely right for them. Principles that guide us: Matching quality is the foundation of therapeutic outcomes — we obsess over getting patients to the right provider We ship fast and learn fast, but we protect patient trust above all else We build for the whole marketplace: patients, providers, and payers ML powers our systems, but empathy drives our product The Problems You'll Solve This role exists because we have hard, specific challenges that need senior engineering leadership to crack. Here's what your first year looks like: Build an ML-powered matching system from the ground up. Our current matching is largely filter-based. We need to move to ML-powered ranking that incorporates provider communication style, expertise signals, and patient outcome data — without degrading the patient experience during the transition. You'll define the technical strategy for how we get there and own the execution across multiple pods. Rearchitect team topology as the product evolves. We have four pods today, but the boundaries between ranking, activation, and onboarding will shift as we move toward intelligent matching. You'll need to evolve team structure, ownership boundaries, and technical interfaces as the product changes shape. This includes scaling the org from ~18 to ~25+ engineers while maintaining velocity and quality. Close the gap between engineering output and patient outcomes. We have patient funnel metrics (intake-to-match, match-to-book, book-to-retained) but engineering doesn't yet co-own them tightly enough with Product and Data. You'll establish the operating model where engineering, product, and data science jointly own these metrics in a true triad — not one where engineering is an execution arm. Define how your teams build software in the AI era. This isn't about adding a bullet point on AI tooling. You'll set concrete standards for how your ~30 engineers use AI-assisted development — how it changes code review, testing strategy, onboarding, and potentially team composition. You'll also own the AI/ML strategy for the product itself: where we use ML models vs. heuristics, how we handle explainability in a healthcare context, and how we build patient trust in AI-driven recommendations.

Requirements

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
Scaled an engineering org through a high-growth phase (25+ to 50+) while maintaining velocity and quality
Technically strong enough to make sound architecture calls on ranking/ML systems, marketplace infrastructure, and consumer-facing surfaces — you don't write code daily, but you can review a system design and spot the problems
Experience shipping ML-powered product features (search ranking, recommendations, personalization) at consumer scale
Track record of moving business metrics (conversion, retention, engagement) through engineering-product partnership, not just delivering features on time
Comfort working in a regulated industry where you can't just ship fast — you need to reason about bias, explainability, and patient safety in ML systems
Practiced perspective on AI-augmented engineering workflows — you've led teams through adoption of AI development tools and have opinions on what changes and what doesn't

Nice To Haves

Healthcare experience or other regulated industries where data sensitivity and clinical consequences raise the stakes
Experience with marketplace dynamics (supply/demand balancing, multi-sided incentive design)
Experience building LLM-based product features (conversational interfaces, intelligent triage, AI-assisted workflows)
Experience rethinking team structure or hiring profiles in response to AI productivity gains

Responsibilities

Set 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
Drive delivery of ML-powered ranking, reimagined patient onboarding, and patient activation systems
Build an engineering culture with clear standards for velocity, quality, and technical excellence — starting with honest assessment of where we fall short today

Benefits

Equity compensation
Medical, Dental, and Vision coverage
HSA / FSA
401K
Work-from-Home Stipend
Therapy Reimbursement
16-week parental leave for eligible employees
Carrot Fertility annual reimbursement and membership
13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st
Flexible PTO
Employee Assistance Program (EAP)
Training and professional development