Director, Engineering (Patient) at headway | AI Job Board

Job description

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 75,000 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, Spark Capital, 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.

We believe AI is the unlock for our next phase — more intelligent matching, more personalized patient experiences, and a fundamentally different way of building software. This role sits at the center of that transition.

About Patient Core Experience at Headway

The Patient Core Experience team is building what we believe will become one of the most consequential AI products in healthcare: a system that connects patients with therapists who are genuinely right for them.

Our four engineering pods — Onboarding, Profiles + Checkout, Ranking + Relevance, and Activation — own the full patient journey from first visit through early retention. Today, our matching is largely filter-based. We're rebuilding it as an intelligent system that uses communication style, data-backed expertise signals, patient-reported outcomes, and behavioral signals to surface the right provider for each patient at the moment they're ready to get help.

We operate a three-sided marketplace (patients, providers, payers) with real complexity and massive impact. The leap from directory to intelligent matching platform is the defining technical challenge for this team. It requires both serious AI/ML product work and a leader who has already made the shift to AI-augmented engineering — and has opinions about what that means in practice.

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

This role exists because we have hard, specific challenges that need senior engineering leadership to crack.

Build the AI-powered matching engine that defines Headway's next chapter. Our current matching is filter-based. You'll own the technical strategy and execution for moving to ML-powered ranking — incorporating provider communication style, clinical expertise signals, and patient outcome data. This means deciding when to use ML models vs. heuristics, how to reason about explainability and bias in a healthcare context, how to A/B test matching quality without degrading patient experience, and how to build patient trust in AI-driven recommendations. Getting this right will directly improve outcomes for every patient on Headway.

Ship AI product features that make the patient journey feel intelligent. Matching is just the start. There's significant opportunity to use LLMs and generative AI to improve how patients understand their options, how we guide them through onboarding and intake, and how we keep them engaged through the early sessions where drop-off risk is highest. You'll own the AI product strategy for your pods — where we go beyond ML ranking into generative and agentic approaches, and how we do it responsibly in a regulated healthcare environment.

Define what AI-era engineering looks like for your teams. You'll set concrete standards for how your ~30 engineers use AI in their workflow — and this isn't a generic "adopt Cursor" mandate. You'll develop a real POV on how AI changes code review, testing strategy, PR standards, onboarding, and what skills you hire for. You've led teams through this transition before and have specific, battle-tested opinions on what changes and what doesn't. You'll be setting the standard, not delegating it.

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 — a true triad, not one where engineering is an execution arm.

Evolve team structure as the product evolves. The boundaries between ranking, activation, and onboarding will shift as we move toward intelligent matching. You'll evolve team topology, ownership boundaries, and technical interfaces as the product changes shape — while scaling from ~18 to ~25+ engineers without losing velocity or quality.

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
Drive delivery of 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
Build an engineering culture that uses AI in the workflow and builds AI into the product — as two distinct, equally important practices

What You Bring

Required:

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
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)

Our Stack

Python (Django/FastAPI) and TypeScript/React on the frontend. Elasticsearch powers search and ranking. PostgreSQL and Redis handle data storage and caching. We use dbt and Snowflake for data pipelines, Temporal for workflow orchestration, and custom ML models for matching. Everything runs on AWS.

For AI development, we use Claude Code and Cursor across the engineering org and are actively evolving our standards for AI-assisted workflows. You'll be setting the direction here, not inheriting a finished playbook.

You won't be writing code daily, but you'll engage deeply enough with these systems to make sound technical and organizational decisions.

You'll Love This Role If You Want To

Build AI products with genuine clinical impact — where better matching means better mental healthcare for real people
Lead the transition to AI-era engineering in practice, not just in principle — with the autonomy to define what that means for your teams
Co-own patient outcomes, not just engineering output
Shape an engineering org during a foundational transition, with strong executive support and a clear mission
Work at a company where the mission isn't marketing copy — patients are actually getting access to therapy they couldn't get before

Compensation and Benefits:

The expected base pay range for this position is $264,000 to $330,000, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential.

Benefits offered include:

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

We believe a team's strength is in its people, and we cannot achieve this mission without a team that reflects the diversity of this problem – across race, ethnicity, gender, sexuality, age, national origin, religion, family status, disability, military status, and experience. Headway is committed to the full inclusion of all qualified individuals. As part of this commitment, Headway will ensure that persons with disabilities are provided with reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or receive other benefits and privileges of employment, please inform the recruiter when they contact you to schedule your interview.

Headway participates in E-Verify. To learn more, click here.

A notice to Headway applicants: To protect yourself against phishing and recruitment fraud, please note that Headway only accepts applications through our official careers page at https://headway.co/careers. Headway will never refer you to external websites, ask for payment or personal information, or conduct interviews via messaging apps. All official communication will come from a @findheadway.com email address. If you are contacted by someone claiming to be from Headway via an unofficial channel, please do not share any information and report it as spam.