Staff Software Engineer, Security & Privacy

About the Role

Abnormal AI is seeking a Staff Software Engineer with deep expertise and passion for Security & Privacy to join the Multi-Product Platform division. 

Security and privacy have become a defining advantage in enterprise software — the companies that invest most deeply in these principles earn the most trust, the largest contracts, and the longest customer relationships. Abnormal AI has built that foundation, and now we need a Staff Engineer to take it further. You will own the division's Security & Privacy vision, driving high-impact initiatives that push our standards across authentication, authorization, and auditability even higher. You will evolve the long-term technical strategies that strengthen customer trust at scale — ensuring Security & Privacy remains an unshakable competitive advantage as the platform grows.

This means identifying and framing business problems, then aligning them with the company objectives, and translating them into clear, actionable technical roadmaps that engineering teams can execute with confidence.

Who you are

• First-principles thinker – you break complex, ambiguous business problems down to fundamental truths, then rebuild them into clear, prioritized milestones that deliver meaningful customer value.
• Pragmatic security mind – you identify and communicate security risks and tradeoffs, and deliver solutions that appropriately balance strong security with real-world business needs.
• Roadmap-to-reality executor - you transform Security & Privacy principles into actionable technical roadmaps, and lead large-scale projects from concept to production with precision and impact.
• AI-native innovator - you bring expertise, passion, and creativity in implementing innovative, AI-native approaches to unlock new capabilities for the division.
• Force multiplier - you foster cross-team collaboration with engineering teams to both seamlessly integrate Security & Privacy best practices into microservice architecture while eliminating implementation overhead for development teams.

What you will do 

• Own the strategic Security & Privacy roadmap for the Multi-Product Platform division across a 3–5 year horizon by partnering with engineering, product, and business stakeholders to define incremental milestones that de-risk execution and unlock tangible business value at each stage.
• Shape technical direction by applying pragmatic security principles and AI-native strategies, ensuring architectural decisions balance robust protection with speed-to-market and evolving business constraints.
• Drive end-to-end delivery of large-scale, cross-functional projects for the Multi-Product Platform division, operationalizing Security & Privacy standards that keep pace with product and market expansion while minimizing overhead and preserving R&D velocity.
• Actively mentor and grow the next generation of Tech Leads - raising the technical bar across the organization, not just within your teams.

Must Haves 

• BS degree in Computer Science, Electrical Engineering, Computer Engineering or other related engineering field.
• 8+ years of professional software engineering experience.
• Strong command of software design fundamentals - including distributed systems, CAP theorem, and system design tradeoffs.
• Deep expertise in Authentication, Authorization, and Security & Privacy problem space, best practices, and related technologies.
• Ability to translate business objectives into actionable technical plans with clear sequencing, dependencies, and success criteria that keep execution aligned with strategic intent.
• Demonstrated history of owning end-to-end delivery of complex projects — navigating ambiguity, managing competing priorities, and consistently shipping high-quality results on time and on-spec across multiple teams and stakeholders.
• Proficiency in Golang and Python programming languages.

Nice to Have 

• Experience in multiple domains - infrastructure, data platform, machine learning, or similar.
• Skill in making reversible versus irreversible technical decisions - and calibrating the right level of rigor for each.
• Contributions to open-source projects, engineering blogs, or industry standards.

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