Qualifications** **Required Qualifications** + Bachelor's Degree AND 5+ years experience in product management, security engineering, or software development OR equivalent experience + Demonstrated hands-on experience with AI/ML systems - you have personally built, evaluated, or shipped ML-powered products or security tools + Deep familiarity with LLM security threats: prompt injection, jailbreaking, data exfiltration, adversarial attacks on generative models - through professional experience, red-teaming, or security research + Experience defining product requirements and driving decisions in partnership with researchers or ML engineers + Track record of building evaluation systems, security benchmarks, or adversarial testing frameworks - not just consuming them + Ability to operate autonomously, make decisions with incomplete information, and drive projects from ambiguity to shipped outcomes **Preferred Qualifications** + Technical background in computer science, security, or AI/ML - a postgraduate degree is a plus but not required + Experience in offensive security, penetration testing, or red teaming - ideally applied to AI/ML systems + Familiarity with security workflows and tooling (SIEM, SOAR, EDR, threat intelligence platforms) and how practitioners use them in production + Understanding of the model lifecycle (pre-training, fine-tuning, RLHF, deployment, monitoring) and where security interventions are most effective + Experience working with or within enterprise security organizations (e.g., Microsoft Security, CrowdStrike, Palo Alto Networks, or similar) + Published research, blog posts, or public contributions in AI security, adversarial ML, or LLM red teaming Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. **Responsibilities** **Responsibilities** + **Own the model security roadmap:** Define and prioritize the security hardening strategy for our frontier models across the full OWASP LLM threat surface - prompt injection (direct and indirect), data exfiltration, jailbreak resistance, system prompt leakage, training data extraction, and adversarial manipulation of agentic workflows.