GenAI Cloud Security Chief Architect

About the Role:
Grade Level (for internal use):
13 The role: GenAI Cloud Security Chief Architect

We are seeking a seasoned GenAI Cloud Security Chief Architect to design, implement, and continuously improve our enterprise AI security posture across all major cloud providers (AWS, Microsoft Azure, Google Cloud Platform, Oracle Cloud Infrastructure) and on-prem/edge environments. This role will own the AI risk framework, perform security architecture reviews for agentic AI systems, and lead the secure design, deployment, and lifecycle management of AI agents (including MCP, ACP, and A2A patterns). The ideal candidate blends deep security engineering experience with modern AI/ML and MLOps/LLMOps knowledge, delivering secure-by-design solutions that are compliant, resilient, and business-aligned.

Key Responsibilities
Strategy & Governance

• Define and operationalize the AI Security Strategy covering models (foundation, open-source, fine-tuned), data pipelines, orchestration layers, agents, and integrations across AWS, Azure, Google Cloud Platform, and OCI.
• Establish and maintain an AI Risk Framework (e.g., NIST AI RMF, ISO/IEC 23894), mapping to enterprise risk taxonomy, control objectives, and regulatory requirements (e.g., SOC 2, ISO 27001, NIST 800-53, CSA CCM).
• Create AI security policies and standards (prompt safety, model access control, agent permissions, data retention, evaluation criteria, provenance & watermarking) and drive adoption across product and platform teams.
• Lead AI Security Governance forums with Legal, Compliance, Privacy, Risk, and Data teams; champion secure-by-design and privacy-by-design principles.

Architecture & Engineering

• Perform Security Architecture Reviews for AI systems:
  • Models: hosted (Azure OpenAI, Bedrock, Vertex AI), self-hosted (Open source, on-prem GPUs), retrieval augmented generation (RAG).
  • Agents: MCP servers, ACP patterns, A2A (Agent-to-Agent) communication, tool/plugin ecosystems, vector DBs, function calling.
  • Pipelines: data ingestion/ETL, feature stores, prompt libraries, guardrails, evaluators, and observability.
• Develop and maintain security reference architectures for multi-cloud AI workloads, including:
  • Identity & Access (IAM, workload identity federation, secrets & key management).
  • Network segmentation, private connectivity, service endpoints, API gateways.
  • Data security (classification, tokenization, encryption, confidential computing, secure enclaves).
  • Model security (supply chain, signing, attestation, integrity verification, model provenance).
• Design and implement agent safety controls: sandboxing, least-privilege tooling, capability constraints, policy enforcement (RBAC/ABAC), prompt injection defenses, jailbreak & prompt-leak mitigation, safe tool-use patterns.
• Build secure AI agents and MCP/ACP/A2A integrations (e.g., tools for enterprise systems like ticketing, knowledge bases, DevOps, and cloud APIs), including:
  • Runtime isolation (containers, microVMs), egress controls, command filtering, and audit trails.
  • Safety guardrails: content filters, toxicity checks, output validation, semantic gateways.
  • Observability: telemetry, tracing, prompt/result logging, risk scoring, red-team feedback loops.
• Embed LLMOps/MLOps security in CI/CD: model artifact scanning, dependency SBOMs, policy-as-code, attestation, and controlled promotion through environments.
• Implement continuous evaluation and guardrails: adversarial prompts, scenario-based testing, safety & accuracy metrics, drift detection, hallucination tracking, bias & fairness assessments.
• Map AI controls to regulatory frameworks (e.g., financial sector, privacy laws including GDPR/CCPA/GLBA).

Stakeholder Enablement

• Partner with Cloud Architecture, Data Science, and Cloud Platform teams to deliver secure AI features at speed without compromising risk posture.
• Educate and enable engineering teams: playbooks, secure coding guidelines for agents, prompt hygiene, model evaluation standards, and threat modeling workshops.
• Communicate risk and value trade-offs to executives; produce clear dashboards and reports on AI security KPIs, incidents, and risk reduction.

Required Qualifications

• 10+ years in Information Security with 4+ years in cloud security and 2+ years in AI/ML or LLMOps security.
• Hands-on multi-cloud expertise:
  • AWS: IAM, KMS, PrivateLink, Bedrock, SageMaker, GuardDuty, CloudTrail.
  • Azure: Entra ID, Key Vault, Private Endpoints, Azure OpenAI, ML, Defender for Cloud.
  • Google Cloud Platform: IAM, KMS, VPC-SC, Vertex AI, Cloud Armor, Audit Logs.
  • OCI: IAM, Vault, Service Gateway, Data Science, Logging & Events.
• Security engineering proficiency: Zero Trust, policy-as-code (OPA/Conftest), secrets management (HashiCorp Vault), container security, SBOMs, SLSA, Sigstore.
• AI/LLM stack knowledge: RAG patterns, vector databases (Pinecone/Weaviate/FAISS), prompt engineering, guardrails (e.g., policy filtering), evaluation frameworks, agent orchestration (MCP/ACP/A2A, function/tool calling).
• Threat modeling and offensive testing for AI systems, including prompt injection and agent misuse.
• Strong understanding of privacy and compliance impacting AI (GDPR, CCPA, GLBA, sector-specific regs).

Preferred Qualifications

• Experience deploying agentic AI in production with secure toolchains and runtime isolation.
• Familiarity with confidential computing (AMD SEV, Intel SGX, Azure Confidential Computing, Nitro Enclaves) and privacy-preserving ML (differential privacy, federated learning, homomorphic encryption).
• Experience with model risk management and AI explainability/traceability (provenance, watermarking, evaluation pipelines).
• Background in financial services or other highly regulated industries.
• Expertise with data governance (catalogs, lineage, quality) and security posture management (CSPM/CNAPP) for AI workloads.

Certifications (Nice to Have)

• CISSP, CCSP, CISM
• Certified Cloud Security Professional (CCSP) equivalents for AWS/Azure/Google Cloud Platform/OCI
• Machine Learning / AI certifications (e.g., AWS ML Specialty, Azure AI Engineer)

Compensation/Benefits Information (US Applicants Only):

S&P Global states that the anticipated base salary range for this position is $166,000 - $213,000. Final base salary for this role will be based on the individual's geographical location as well as experience and qualifications for the role.
In addition to base compensation, this role is eligible for an annual incentive plan. This role is not eligible for additional compensation such as an annual incentive bonus or sales commission plan.

This role is eligible to receive additional S&P Global benefits. For more information on the benefits we provide to our employees, please click here .

What's In It For You?

Our Mission:
Advancing Essential Intelligence.

Our People:
We're more than 35,000 strong worldwide-so we're able to understand nuances while having a broad perspective. Our team is driven by curiosity and a shared belief that Essential Intelligence can help build a more prosperous future for us all.From finding new ways to measure sustainability to analyzing energy transition across the supply chain to building workflow solutions that make it easy to tap into insight and apply it. We are changing the way people see things and empowering them to make an impact on the world we live in. We're committed to a more equitable future and to helping our customers find new, sustainable ways of doing business. Join us and help create the critical insights that truly make a difference.

Our Values:
Integrity, Discovery, Partnership

Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals.

Benefits:
We take care of you, so you can take care of business. We care about our people. That's why we provide everything you-and your career-need to thrive at S&P Global.

Our benefits include:

• Health & Wellness: Health care coverage designed for the mind and body.
• Flexible Downtime: Generous time off helps keep you energized for your time on.
• Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.
• Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.
• Family Friendly Perks: It's not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.
• Beyond the Basics: From retail discounts to referral incentive awards-small perks can make a big difference.

For more information on benefits by country visit:

Global Hiring and Opportunity at S&P Global:
At S&P Global, we are committed to fostering a connected and engaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets.

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Equal Opportunity Employer
S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment.

If you need an accommodation during the application process due to a disability, please send an email to: and your request will be forwarded to the appropriate person.

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103 - Middle Management (EEO Job Group) (inactive), 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group)