AI Security Engineer, Defensive Automation

5 дн. назад

СШАHybrid

Build automated, AI-driven systems to find, prioritize, and fix security weaknesses faster than attackers.

, the agentic law company, has a client base with a combined $30 trillion in assets under management.
pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain-specific AI agents with Norm’s proprietary suite of no-code software tools. technology is deployed inside many of the largest and most consequential institutions in the world.
is also the technology behind Norm Law, LLP, a separate but affiliated AI-native law firm built for the era of agentic AI. Norm Law’s attorneys advise leading institutions across private funds, private equity, venture capital, real estate, registered funds, and financial regulation, using the same legal intelligence platform that powers ’s products. AI Fluency: prefers all team members to be fluent in AI. Successful candidates actively use AI in their day-to-day work to support thinking, creation, and problem-solving. They use it to improve the quality and speed of their work and to continuously refine how work gets done end-to-end. Candidates should be prepared to demonstrate and discuss their AI usage throughout the interview process, including concrete examples of tools, workflows, and outcomes. We look for practical, hands-on experience, not theoretical familiarity.

Build defensive automation: Design, build, and improve AI-driven security tooling, with the testing, safeguards, and human oversight you’d expect of production systems.
Threat-model: Assess new and existing systems for risk, and use those models to decide where detection and remediation effort goes.
Respond to incidents: Join the response rotation for critical vulnerabilities and security events, from assessing exposure through remediation.
Measure and communicate: Track how well our security work is performing, and explain risks and tradeoffs clearly to technical and non-technical audiences.

Strong software engineering skills, with production code in at least one modern language
Hands-on experience building with LLMs or AI agents
Solid application security and cloud security fundamentals
Experience running threat models
Calm, structured judgment during incidents

Base Salary : $155,000 to $215,000 per year
The range displayed in this job posting reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by various factors, including job-related skills, experience, and relevant education or training.
Equity: Included
Benefits: 401(k) with employer match, health, dental, vision coverage, unlimited paid time off, free lunch in office daily, employee referral bonus program
Relocation: Financial support to ease your move to New York City, designed to make the transition smooth and stress-free.
Location / Office Requirement: Washington, DC (preferred), New York City
Work model: Hybrid
Travel expectation: Travel to NYC headquarters at least once per quarter
To learn more about , visit our website .

We’re hiring AI Security Engineers to build automated, AI-driven systems that find, prioritize, and fix security weaknesses faster than attackers can exploit them.
You’ll work across the full lifecycle, from discovery and threat modeling through remediation and response, and go deep in either offensive research or defensive operations based on your strengths. You’ll report to the Chief Security Officer and work closely with Engineering.
Find unknown weaknesses: Proactively hunt for previously unknown weaknesses using both automated and manual techniques, in a safe and controlled way.
Validate findings: Confirm and reproduce findings, and feed what you learn back into the automation to make it better.
Run vulnerability management at scale: Triage, prioritize, and remediate vulnerabilities, automating as much of the process as you can.
Turn threat information into priorities: Bring threat intelligence and external advisories into decisions about what gets fixed first.
Research: Vulnerability research, offensive security or red teaming, exploit development, CVE credits, or bug bounty work
Operations: Vulnerability management at scale, detection and response, security automation, or software supply-chain security