[Remote] Technical Consultant - Data and AI Security

Note: The job is a remote job and is open to candidates in USA. IBM is seeking an AI Security Architect for its consulting work with clients. The role leads the design, assessment, and governance of secure AI/ML systems, including AI security architecture, governance frameworks, threat modeling, vendor risk assessments, and red-team exercises.

Responsibilities

• Design and advise Clients on enterprise-wide security reference architectures for AI/ML systems — LLMs, generative AI pipelines, ML inference infrastructure
• Establish secure-by-design patterns for model training, data pipelines, model registries, APIs, and AI-enabled applications
• Define security controls for AI infrastructure across cloud, on-prem, and hybrid environments (Azure, AWS, GCP)
• Develop and enforce the organization's AI Governance Framework, including acceptable use policies, model risk management, data ethics, and accountability structures
• Align AI governance programs with regulations and standards: EU AI Act, NIST AI RMF, ISO/IEC 42001, OWASP LLM Top 10, MITRE ATLAS
• Define AI risk tiers and corresponding control requirements (high-risk vs. limited-risk AI systems)
• Establish model cards, AI Bill of Materials (AI-BOM), and audit trail requirements for deployed AI systems
• Partner with Legal, Privacy, and Compliance on regulatory obligations for AI across domains
• Lead AI-specific threat modeling using MITRE ATLAS, OWASP LLM Top 10, and adversarial ML taxonomies
• Conduct assessments covering: data poisoning, model inversion, adversarial evasion, prompt injection, training data extraction, supply chain risks, and model theft
• Assess AI/ML vendor products and third-party AI integrations for security posture and governance maturity
• Co-ordinate and run red team exercises — LLM jailbreaking, API abuse, agentic AI manipulation scenarios
• Produce written assessment reports with risk ratings, findings, and remediation roadmaps for technical and executive audiences

Skills

• 7+ years in cybersecurity, with 3+ years focused on AI/ML security, data science security, or emerging technology risk
• Deep understanding of ML concepts: model training, inference, fine-tuning, RAG architectures, agentic AI, and LLM deployment
• Hands-on experience with AI/ML threat modeling and adversarial attack techniques (data poisoning, prompt injection, adversarial examples, model extraction)
• Familiarity with AI governance frameworks: NIST AI RMF, ISO/IEC 42001, EU AI Act, OWASP LLM Top 10, MITRE ATLAS
• Strong background in cloud security architecture (AWS, Azure, or GCP) — IAM, data security, network controls
• Experience conducting security architecture reviews, risk assessments, and writing executive-level reports
• Excellent written and verbal communication — ability to translate complex AI risks into business-relevant language
• Experience with MLOps platforms (MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML)
• Programming skills in Python for scripting, security automation, or ML experimentation
• Prior experience building or auditing Responsible AI / Trustworthy AI programs
• Experience with AI supply chain security — model provenance, SBOM/AI-BOM, open-source model vetting
• Background in regulated industries (finance, healthcare, government)
• Relevant certifications: CISSP, CCSP, CISM, AWS/Azure/GCP Security Specialty, or GIAC certifications

Benefits

• This role can be performed from anywhere in the US.

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