Tech Lead Manager Identity Security
Abnormal AI
Job Overview
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Job Description
About The Role
Abnormal AI is building the platform to secure a new reality where enterprises are undergoing two simultaneous transformations: moving critical infrastructure to the cloud and adopting AI agents at scale. These shifts create an identity explosion, with humans, service accounts, and AI agents now vastly outnumbering traditional users. Legacy tools struggle to govern the permissions of these identities. Abnormal's Identity Security team is developing a solution with unified visibility across all identity types, behavioral intelligence to understand normal activity, and AI-native automation operating at cloud speed. We are extending our proven behavioral approach from email security to protect identities across cloud infrastructure and AI systems.
The Identity Security team is seeking a Tech Lead Manager Identity Security to build and lead this critical product area. You will begin hands-on with a small team, actively contributing code while evolving the product towards market fit. This role requires you to be located in the San Francisco Bay Area and able to work 25% in office.
What You'll Do
- Lead a team of 2-4 engineers, writing and reviewing code daily alongside them.
- Collaborate closely on technical direction and establish foundations for a scalable product.
- Partner directly with internal and external customers to gather feedback and iterate quickly.
- Grow the team and product as we gain traction and expand our scope.
- Set engineering standards and practices that will scale with team growth.
This Role Is a Fit If You
- Want to be deeply technical while developing leadership skills, excited to code, not just manage.
- Thrive in ambiguity and can guide a small team through uncertainty toward product-market fit.
- Possess strong instincts for customer needs and translate them into effective product decisions.
- Enjoy the founding-team dynamic: small group, high ownership, fast iteration.
This Role Is Not a Fit If You
- Prefer managing established teams with well-defined roadmaps.
- Want to step back from hands-on technical work.
- Are uncomfortable with the ambiguity inherent in an early-stage product.
Requirements
- 5+ years of software engineering experience with 1+ year in a tech lead or engineering management role.
- Proven track record of shipping products in fast-moving environments.
- Ability to read, write, and review code at a high level (Python/Go preferred).
- Experience hiring and developing engineers.
- Bay Area location required, with 25% in-office presence.
Preferred Qualifications
- Experience building enterprise/B2B security products.
- Familiarity with machine learning systems or ML-adjacent infrastructure.
- Exposure to AWS, Kafka, containerized services, and microservices.
Growth Paths
- Expand scope as Identity Security grows, taking on additional product lines.
- Build out a larger team as we scale beyond initial product-market fit.
- Position yourself for senior leadership as the organization matures.
What We Offer
The opportunity to join a veteran team that has built enduring ML platforms at leading tech companies. Our customer base includes multiple Fortune 500 companies, and Identity Security is a critical bet for Abnormal AI's future. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $187,900—$254,000 USD.
Key skills/competency
- Identity Security
- Software Engineering
- Team Leadership
- Python/Go
- Cloud Infrastructure
- Product Development
- Behavioral Intelligence
- AWS
- Microservices
- Machine Learning
How to Get Hired at Abnormal AI
- Research Abnormal AI's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight your experience in identity security, team leadership, and hands-on coding (Python/Go) to match the Tech Lead Manager Identity Security role requirements precisely.
- Showcase technical depth: Prepare to discuss your experience with cloud infrastructure, AI/ML systems, and microservices during technical interviews.
- Demonstrate leadership potential: Be ready to share examples of guiding teams through ambiguity, setting engineering standards, and fostering product growth.
- Articulate customer focus: Practice explaining how you translate customer feedback into product decisions and drive rapid iteration for market fit.
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