Staff Security Engineer, Detection & Response

Maven Clinic is a virtual clinic focused on improving healthcare access and outcomes for women and families. The Staff Security Engineer will own the Incident Detection and Response program, lead investigations, identify and remediate security weaknesses, develop detection logic, harden the SDLC, and manage risks related to AI and LLM-powered systems.

Responsibilities:

• 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
• 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
• 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
• 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

Requirements:

• 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
• 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