Jobs
Benefits & Perks
•Flexible work arrangements
•Competitive salary and equity package
•Comprehensive health, dental, and vision insurance
•Team events and activities
•Flexible Hours
•Equity
•Healthcare
Required Skills
Python
JavaScript
React
About the Role
Enterprises are undergoing two simultaneous transformations: moving critical infrastructure to the cloud and adopting AI agents at scale. Both create an identity explosion—humans, service accounts, and AI agents now outnumber traditional users 10-to-1, each with permissions that legacy tools can't govern. Abnormal's Identity Security team is building the platform to secure this new reality: unified visibility across all identity types, behavioral intelligence that understands what's normal, and AI-native automation that operates at cloud speed. We're extending the same behavioral approach that made Abnormal the leader in email security to protect identities across cloud infrastructure and AI systems.
What you will do
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Build discovery, classification, monitoring, and protection for machine identities and their agentic actions.
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Ship guardrails and policy engines that enable safe automation while preventing misuse, escalation, and anomalous behavior.
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Create high‑availability pipelines that ingest and correlate identity, authorization, and behavioral signals from cloud, SaaS, IAM/SSO, and audit logs.
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Drive 0→1 iteration: prototype quickly, test assumptions, learn from usage, and scale simple solutions.
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Collaborate across security, platform, and data teams; write and review technical designs; and participate in core SDLC rituals.
Must Haves
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2+ years building software applications.
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Experience productionizing large‑scale, data‑intensive systems.
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High velocity and creativity in solving technical challenges.
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Experience & desire to adopt & improve AI-native development workflows.
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Strong debugging with logs, metrics, and signals.
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Ability to translate business requirements into high‑quality software.
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Ability to independently solve complex problems and work cross‑functionally.
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BS in CS/SE/IS or related field.
Nice to Have
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Experience with Go and Python.
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Experience in IAM, non‑human/machine identities, secrets management, workload identities, OAuth/OIDC, SCIM, SSO, or policy engines.
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Experience in cybersecurity or related industries.
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Experience with big data, statistics, and ML for identity/behavioral risk modeling.
At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.
Base salary range:
$148,800—$175,000 USD
Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
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About Abnormal Security

Abnormal Security
Series BSoftware company.
201-500
Employees
Miami
Headquarters
$4B
Valuation
Reviews
4.2
16 reviews
Work Life Balance
4.0
Compensation
4.5
Culture
4.3
Career
4.5
Management
3.7
87%
Recommend to a Friend
Pros
Competitive compensation packages with equity
Strong engineering culture with focus on code quality
Flexible remote work options and good work-life balance
Cons
Some legacy systems that need modernization
Internal politics in some teams
Organizational changes and restructuring can be disruptive
Salary Ranges
64 data points
Senior/L5
Senior/L5 · Senior Manager of Customer Success
1 reports
$202,412
total / year
Base
$176,010
Stock
-
Bonus
-
$202,412
$202,412
Interview Experience
1 interviews
Difficulty
1.0
/ 5
Duration
14-28 weeks
Experience
Positive 0%
Neutral 0%
Negative 100%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common Questions
Behavioral/STAR
Technical Knowledge
Culture Fit
Past Experience