AI Security Operations; SecOps) Specialist

Are you ready to secure and scale an enterprise Agentic AI ecosystem that protects data, accelerates science and ultimately helps deliver life-changing medicines? Do you want to transform “AI for Cyber” and “Cyber for AI” ideas into dependable, high-impact services that safeguard our people and platforms?

In this hands-on technical leadership role, you will sit at the intersection of security operations, agent engineering, AI platform security and intelligent automation. You will operate the AI security control plane, harden agentic systems across their lifecycle, and establish monitoring and response that makes agent behavior observable, safe and auditable. You will be empowered to take ownership from day one—designing secure patterns, building production-grade automations and guiding the roadmap as platforms, models and attack techniques evolve.

Accountabilities:

• Agentic AI Platform Security and Control Engineering:
  Define, implement and continuously improve controls for agent identity, authentication and authorization; the least agency; tool access; data boundaries; memory governance; inter-agent communications; runtime policy enforcement; human approval gates; auditability and emergency containment.
• Secure Patterns and Guardrails:
  Create reusable secure patterns, reference configurations, guardrails and policy-as-code that teams can adopt without redesigning security for each use case.
• Architecture Assurance:
  Assess agent architectures and workflows; embed security into onboarding, design reviews, solution blueprints, threat models, release gates and production readiness; validate controls through testing, abuse-case analysis and red/purple-team exercises.
• Agent Lifecycle Operations:
  Own or coordinate secure lifecycle from discovery and registration through build, test, approval, deployment, monitoring, change, suspension and retirement; maintain inventory of owners, purpose, autonomy, privileges, data access, dependencies, risk tier and control posture.
• Workflow and Orchestration Reliability:
  Govern multi-agent dependencies, delegated actions, retries, approvals, exception handling and fail-safe behavior; drive secure, supportable integration of agents with enterprise platforms and Cybersecurity services via governed APIs and service identities.
• AI Security Observability:
  Build telemetry strategies that reconstruct agent intent and actions—including prompts and instructions where policy permits—tool calls, identities, memory updates, policy decisions, outputs, errors and outcomes; integrate with SIEM, SOAR, EDR/XDR, cloud, identity, data protection, application security and case-management platforms.
• Detection and Response:
  Design, tune and operationalize detections for AI-specific threats and control failures; lead or support triage, containment, eradication, recovery and post-incident improvement; codify automated response playbooks including safe pause, tool and credential revocation, network isolation, rollback, kill-switch activation, evidence preservation and escalation.
• AI for Cyber and Cyber for AI Automation:
  Lead the portfolio that uses agents to improve assessment, threat modeling, detection engineering, vulnerability analysis, incident response and reporting; embed security checks, risk scoring, control validation and approvals into AI/ML and agent delivery workflows; build agents and orchestrations in Python with secure engineering, CI/CD and production support; measure value through cycle-time, quality, coverage, analyst effort avoided, risk reduction and reliability
• Security Operations and Platform Stewardship:
  Provide technical oversight for day-to-day operation of AI security capabilities, ensuring health, telemetry completeness, integration fidelity, detection coverage…