Staff Software Engineer (Journeys)

About engineering at Headway:

• Building a new mental healthcare system at Headway is only possible because of the scale and leverage that software can provide. The engineering team at Headway is a small but mighty team using technology to build that future (and have a fun time while doing it!).

Principles that guide us:

• Focus on the mission: We view software as a means of effecting change in the world, not as an end unto itself. We write software to empower our patients and therapists to better solve the problems they’re facing.

• Ship small, learn fast: We are building new and novel products and believe that we learn what our users need by quickly shipping and iteration

• Everything is a product: Whether it's our patient search experience or a developer productivity improvement, we treat everything we build at Headway as a product with end-users in mind.

• Optimize for trust: We believe that engineers should be continually learning. To learn effectively and to be productive, engineers must feel safe asking questions and discussing mistakes.

Tools we use:

• Languages: Python 3, TypeScript

• Libraries & Frameworks: FastAPI, SQLAlchemy, React, Remix, Next.js

• Datastores: Postgres, Redis

• Infrastructure: AWS (Fargate, ECS, S3, and more), Spark and Kafka

• Monitoring: Datadog, PagerDuty, Sentry

• Version Control: Github, PagerDuty

• Vulnerability Management: Snyk, Semgrep

• Cloud Security: Lacework

• Delivery: Knock (transactional + product notifications), Iterable (lifecycle marketing + campaigns), Twilio, Mailgun

About the Journey Team at Headway

• The Journey team powers how Headway reaches every patient and provider at the right moment, on the right channel - email, SMS and other communication channels. We’re building the next chapter: an agentic communications engine that learns which message, which channel, and which timing works best for each person — and gets smarter with every send. We own the full stack: from the delivery layer (Knock for transactional, Iterable for lifecycle), to the decision engine we’re building today.

• About this role

  • We’re looking for a Staff Engineer to be the technical anchor of the Journey team. This is a senior IC role — the person who owns the architecture of how Headway communicates at scale. You’ll design and evolve the decision engine, experimentation layer, and channel orchestration that will define how Headway reaches patients and providers for years to come. You’ll set the technical direction for a multi-vendor communications stack, own the unified message ledger, and bring LLM-powered personalization from concept to production.

  • This role is high-leverage and cross-functional. You’ll work closely with marketing, CX, product, and the patient org — and your work will directly impact patient acquisition, retention, and health outcomes.

Who you are:

• We’re looking for experienced engineers who have the ability to deal with ambiguity and learn new technologies and systems. Below are some additional experiences we think help engineers succeed at Headway.

  • A systems thinker who holds the architecture of a complex, multi-vendor platform and guides the team through it

  • An engineer who has shipped high-throughput, event-driven systems in production and knows what reliability requires

  • A communicator who translates technical trade-offs for non-technical stakeholders and drives alignment across marketing, product, and engineering

  • Genuinely excited about the intersection of AI and communications — and thoughtful about what makes AI-in-the-loop systems reliable at scale

  • A leader who earns influence through technical depth and leaves teams more capable than they found them

• Experience we’re seeking

  • 8+ years of software engineering experience, with meaningful time at Staff-level or equivalent

  • Designed and built high-volume, event-driven communications platforms — email, SMS, push, or equivalent — at millions of events per month

  • Fluency with multi-vendor delivery stacks; strong opinions about build-vs-buy trade-offs at the platform layer

  • Experience building or working closely with experimentation infrastructure — A/B testing, engagement analytics, personalization, or recommendation systems

  • Exposure to LLM-powered systems in production — not just API consumption, but thinking about reliability, latency, and quality at scale

  • Demonstrated ability to shape technical direction across teams without direct authority