Technical Consultant - Data and AI Security

International Business Machines Corporation; Nevada; Remote; USD 190,000 - 270,000; Full time

Job summary

IBM Consulting is seeking an AI Security Architect to lead security design and governance for AI/ML systems across enterprise environments. You will work with data science, engineering, legal, and leadership to define trustworthy AI—from threat modeling to policy enforcement and vendor risk.

This role can be performed from anywhere in the US. Responsibilities include developing enterprise security references for AI, enforcing governance, and guiding risk assessments and remediation.

Qualifications

• 7+ years in cybersecurity, with 3+ years focused on AI/ML security or data science risk.
• Deep understanding of ML concepts including training, inference, and deployment.
• Hands-on experience with AI threat modeling and adversarial techniques.

Responsibilities

• Design enterprise-wide security reference architectures for AI/ML systems (LLMs, AI pipelines).
• Establish secure-by-design patterns for model training, data pipelines, and APIs.
• Define controls for AI infrastructure across cloud, on‑prem, and hybrid environments.
• Lead AI security assessments and produce risk-based remediation roadmaps.
• Coordinate red team exercises and produce executive-facing reports.

Skills

Security architecture

Threat modeling

AI/ML security

Cloud security

Governance & risk

Executive communication

Regulatory compliance

Security assessments

Tools

MLflow

Kubeflow

SageMaker

Vertex AI

Azure ML

Job description

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact.

Your role and responsibilities

We are seeking a visionary AI Security Architect to lead the design, assessment, and governance of security frameworks for AI/ML systems across the enterprise. You will be the subject matter expert at the intersection of artificial intelligence, cybersecurity, and regulatory compliance — ensuring AI systems are built, deployed, and operated securely and responsibly.

You will work across Client's cross-functionally with data science, engineering, legal, compliance, and executive leadership to define how the organization builds trustworthy AI — from threat modeling to policy enforcement to third-party AI vendor risk.

Key Responsibilities

AI Security Architecture

• 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).

AI Governance & Policy

• 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.

AI Security Assessments

• 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.

This role can be performed from anywhere in the US.

Required technical and professional expertise

• 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.

Preferred technical and professional experience

• 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.

IBM is committed to creating a diverse environment and is proud to be an equal‑opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.