Level

AstraZeneca

AI Security Operations (SecOps) Specialist

AI in this role

ragml-opsai-automation

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 and continuous service improvement; partner across SOC, cloud, identity, data, application security, DevSecOps, MLOps, platform engineering and architecture; deliver executive-ready dashboards and reporting.
  • Governance, Risk and Regulated-Environment Assurance: Translate policy, regulatory and framework expectations into testable requirements and operational evidence; contribute to threat modeling and risk assessment using leading frameworks; support risk-tiered controls across research, business, regulated and GxP-relevant use cases; document residual risk, control limitations, exceptions and approvals to enable defensible decisions; engage vendors and peers to evaluate capabilities and shape adoption roadmaps.

Essential Skills/Experience:

  • Bachelor’s degree in Cybersecurity, Computer Science, Software Engineering, Data Science, Information Systems or a related field, or equivalent relevant experience
  • Proven experience in Cybersecurity engineering, security operations, automation, platform engineering, AI/ML engineering or a closely related field, including meaningful hands-on work securing or operating Generative AI or Agentic AI solutions
  • Proven ability to build production-quality automation or agents using Python; experience with APIs, event-driven workflows, testing, source control, CI/CD and operational support
  • Practical knowledge of agent architectures, LLM applications, RAG, tool calling, memory, orchestration, multi-agent patterns, MCP/A2A concepts and associated security risks
  • Hands-on experience with security monitoring, detection engineering, incident response and automation using SIEM/SOAR and relevant cloud, identity, endpoint, data or application security telemetry.
  • xperience defining and validating controls for cloud and AI platforms, preferably across two or more of Azure, AWS and Google Cloud
  • Strong understanding of identity and access management, secrets and token security, API security, Zero Trust, secure software delivery, threat modeling and least privilege or least agency
  • Ability to turn ambiguous problems into practical architectures, backlogs, controls, code, runbooks, metrics and partner decisions
  • Excellent written and verbal communication, including the ability to explain complex AI security issues to engineers, risk partners and senior leaders.

Here, your craft will directly influence how quickly and safely we bring new treatments to patients. You will work with leading AI platforms and modern engineering practices, side by side with scientists, security specialists and data engineers, turning ambitious ideas into scalable, secure reality. With meaningful investment, a culture that backs experimentation and learning, and a community that values kindness alongside ambition, we bring a diverse set of minds together to spark new thinking, move with speed and build technology that truly matters.


Take the lead in shaping how secure Agentic AI scales in the real world—join us to build the guardrails, automations and response capabilities that power confident innovation today.


#Cyber

Date Posted

22-Sept-2026

Closing Date

27-Sept-2026

Our mission is to build an inclusive and equitable environment. We want people to feel they belong at AstraZeneca and Alexion, starting with our recruitment process. We welcome and consider applications from all qualified candidates, regardless of characteristics. We offer reasonable adjustments/accommodations to help all candidates to perform at their best. If you have a need for any adjustments/accommodations, please complete the section in the application form.

How we score this

AI Security Operations (SecOps) Specialist at AstraZeneca scores 69 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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