Senior Software Engineering Manager | Applied AI Engineering
$190,900–$334,100 year
RemoteUnited States
Job Summary
Own AI-Powered Security Architecture by setting technical strategy for use cases across cyber defense domains like threat intelligence, hunting, and incident response. Unify data into defender-ready systems by leveraging internal telemetry and external intelligence to enable domain-specific automation. Empower security practitioners to extend and maintain these tools independently, compounding team impact over time. Build a high-performing engineering team by recruiting talent, establishing career paths, and holding the group to high technical standards. Drive shipping velocity by owning architecture decisions and removing blockers to ensure rapid, low-risk delivery. Partner cross-functionally with Security Operations, Threat Intelligence, and Red Teams to shape the roadmap. Establish engineering best practices and operationalize threat intelligence to turn security issue management into measurable risk reduction.
Required Qualifications
- Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving
- 10 to 15 years building and shipping software systems at scale (backend, full stack, data, or platform engineering) OR similar experience with education
- Proven track record of building or scaling a high-performing engineering team, with 2+ years managing engineers
- Deep technical fluency: you can code review, evaluate architecture tradeoffs, and unblock the hardest problems your team faces
- Demonstrated ability to distinguish "build it ourselves" from "enable someone else to build it": this role demands both engineering execution and a coaching mindset
- Comfort operating with significant ambiguity, standing up a new function from the ground up
- A track record of establishing engineering best practices and holding a team to a high bar of technical excellence
Desired Qualifications
- Security domain experience (incident response, SOC, threat intelligence, hunting, vulnerability management, etc.), or a strong appetite to learn it quickly
- Experience applying AI/ML to operational or workflow automation at scale
- Familiarity with modern data infrastructure
- Experience building enablement programs, internal platforms, or tooling for non-engineer end users
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