Security Engineer (Detection & Response)
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 90,000 providers across all 50 states run their practice on our software, serving over 2.6 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, and building much of it with AI. 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 the role
The Security team at Headway is responsible for the security and privacy of all of Headway's customers — therapists, patients, and payer partners (insurance companies and health systems). As a Security Engineer on our Detection & Response team, you'll help build the capabilities we use to identify, respond to, and contain potential threats across our production and corporate environments — ensuring our logging is adequate and accessible, our detections cover real-time monitoring and alerting, and our incident response is well-documented and well-rehearsed.
This role scales alongside the volume of data our business generates and consumes, and alongside our ambition to work smarter — not just harder — by applying automation and AI where it genuinely helps, and knowing when it doesn't.
What you'll do at Headway
Detection engineering: Build and refine detections, logging/telemetry coverage, and tooling (SIEM/ETL pipeline refinement) so we have real-time visibility into anomalous and malicious activity across cloud, corporate, and SaaS environments.
Incident response engineering: Run incident response activities, threat hunting, and threat modeling — and continuously improve our processes and documentation so the team gets faster and sharper after every incident.
AI security tooling and automation: Implement automation and AI where it's the right tool for the job — and push back when it isn't. You'll help define what "AI-forward" detection and response looks like at Headway without over-rotating on it.
Security alert triage: Triage security alerts and build deep familiarity with our environment so you can separate signal from noise quickly.
Team contributions: Participate in the security on-call rotation, author runbooks, contribute to security education and partnership across engineering, and mentor peers.
Documentation: Keep detections, logging capabilities, runbooks, response processes, and threat intel well-documented so knowledge compounds across the team.
Tools we use
Languages: Python 3, TypeScript
Infrastructure: AWS (Fargate, ECS, S3, and more)
Datastores: PostgreSQL, Snowflake
Monitoring & Response: Datadog, PagerDuty
Version Control: GitHub
Security Tooling: Anthropic, Wiz, Semgrep, Datadog, Tines
You’ll be great for this role if you have
Dedicated experience of 1-2+ years with responsibilities related to security response and automation OR a security-adjacent engineering background
4-5+ years in related areas — DevOps, IT, software engineering, or similar with concrete security responsibilities or overlap. Comfortable scripting/coding to build and automate your own tooling.
SIEM/observability experience: You've worked with logging, detection, or observability platforms in a cloud or distributed environment. The specific stack matters less than your understanding and approach.
Sound judgment on AI and automation: You're willing to implement AI and automation where it helps, and just as willing to recognize when a deterministic tool — or a human — is the better call.