Staff Security Engineer, Detection

Maven Clinic is the world's largest virtual clinic for women and families on a mission to make healthcare work for all of us. Through Maven Enterprise, the company partners with more than 2,300 employers and health plans to provide end-to-end women's and family health programs spanning fertility and family building, maternity and newborn care, parenting and pediatrics, and menopause and midlife — improving clinical outcomes, reducing healthcare costs, and expanding equitable access to high-quality care at scale. Through its consumer platform, Maven provides direct access to virtual care across 30+ specialties, as well as dedicated hormone and GLP-1 care programs purpose-built for women. Founded in 2014 by CEO Kate Ryder, Maven Clinic has raised more than $425 million from leading healthcare and technology investors including General Catalyst, Sequoia, Dragoneer Investment Group, Oak HC/FT, StepStone Group, Icon Ventures, and Lux Capital. Recognized for innovation and industry leadership, Maven has been named to the TIME100 Most Influential Companies, CNBC Disruptor 50, Fast Company's Most Innovative Companies, and FORTUNE Best Places to Work. Learn more at mavenclinic.com

An award-winning culture working towards an important mission – Maven Clinic is a recipient of over 30 workplace and innovation awards, including: TIME 100 Most Influential Companies (2023, 2026) Fortune Change the World (2024) CNBC Disruptor 50 List (2022, 2023, 2024) Fortune Best Workplaces for Millennials (2024) Fortune Best Workplaces in Health Care (2024) Fast Company Most Innovative Companies (2020, 2023) Fortune Best Workplaces NY (2020, 2021, 2022, 2023, 2024)

About the Role

You'll own our Incident Detection and Response program, including threat modeling our systems and codebase and directing the investigation when something does happen. You'll join a team that includes an AppSec-focused engineer and an infrastructure-focused engineer, and you'll guide technical direction and judgment calls. You'll spend most of your time finding bugs in our code and gaps in our SDLC before they become incidents, then building and implementing or project managing the fixes yourself. AI is a growing part of that surface, and as our reliance on LLMs, AI-generated code, and agents expands, you'll be responsible for understanding and managing the risk that comes with it. What You'll Own

Investigation & Technical Direction

Lead investigations hands-on. When an incident or suspicious finding comes up, you pull the logs, build the narrative of what happened, and advise business and engineering leaders on next steps. Read production code when needed to understand what's actually happening. Proactive Hunting & SDLC Hardening

When you're not investigating, hunt for bugs in our codebase and weaknesses in our SDLC where problems can slip past existing controls. Propose and implement fixes yourself, or manage the resolution with the right teams, whether that's a specific code fix, a broader process or control change. Partner with our Product Security Engineer on golden paths when a weakness points to a systemic gap. Detection Engineering

Own and tune the detection logic running through 7AI, validating its investigations and escalations and setting the criteria for what triggers an alert. Close gaps in logging and visibility so the tooling has the right data to work with. Managing AI Risk

Help us understand and manage the security risks that come with our growing use of LLMs and AI tooling, both in what we build and what we adopt internally. What We're Looking For

Required: 6+ years of security experience combining hands-on software or AppSec depth with detection and SIEM engineering ownership. Comfortable reading production code across multiple languages and stacks well enough to judge whether a finding is actually exploitable. Experience building threat models of codebases, reasoning about attack surface, trust boundaries, and data flow well enough to anticipate where problems will emerge. A track record of finding and fixing systemic weaknesses, whether they surfaced through an incident or through your own proactive review. Strong communication skills, with enough credibility to direct an investigation and influence peers informally. Strongly preferred: Hands-on experience with AI-assisted security operations tooling, such as AI SOC platforms, LLM-based triage, or agentic escalation systems. Interest or experience in securing AI and LLM-powered systems, including risks like prompt injection, model misuse, or agentic tool abuse. Prior exposure to golden-path or secure-by-default infrastructure initiatives, even in a supporting role. Experience with container or image security and the patching lifecycle. A relevant certification such as GCIH, GCFA, GCDA, OSCP, or CISSP. The base salary r