AI Security Analyst

About the Role

As an AI Cyber Strategy & Architecture Consultant in Deloitte Cyber for AI practice, you will help clients build foundational AI security strategies, reference secure AI architectures, and governance frameworks needed to adopt AI securely and at scale. Working alongside experienced architects and senior practitioners, you will contribute to the design and delivery of AI security blueprints, threat models, and compliance alignment programs that span cloud, data, identity, and agentic systems. The role blends rigorous technical analysis with structured client engagement and hands-on delivery.

Key Responsibilities

• Translate regulatory and framework requirements, including NIST AI RMF, EU AI Act, and ISO 42001 Controls, into practical, implementable security controls across AI platforms and data pipelines.
• Assess clients’ AI cybersecurity posture against their business environment, objectives, and risk appetite; identify key strengths and gaps, and develop prioritized recommendations aligned to their constraints and priorities.
• Evaluate AI-specific risks through structured risk assessments and threat modeling, including prompt injection, data leakage, model supply chain compromise, and agentic privilege escalation scenarios.
• Translate assessment findings into enterprise AI security roadmaps by mapping current-state capabilities to target-state architectures, defining required controls, and documenting sequenced remediation actions.
• Contribute to the development, review, and updating of cybersecurity policies, standards, and procedures to incorporate AI-specific risks and controls.
• Contribute to the development of AI security reference architectures covering LLM deployment patterns, RAG pipelines, vector databases, agentic workflows, and model-serving architecture.
• Develop impactful reports and presentations that support the achievement of engagement goals and objectives.
• Collaborate with client engineering, security operations, and business stakeholders to validate architecture decisions and ensure alignment with enterprise security standards.

Key Skills

• Takes ownership of assigned workstreams and deliverables, managing time and quality with minimal oversight while keeping senior colleagues informed of progress and blockers.
• Communicates complex technical architecture and risk concepts clearly in written and verbal formats, adapting the level of detail for engineering teams and business stakeholders alike.
• Approaches unfamiliar AI platforms, frameworks, and threat vectors with structured curiosity - decomposing problems, researching quickly, and applying findings to real client contexts.
• Demonstrates a delivery-first mindset, consistently producing high-quality work products on schedule and proactively flagging risks to project timelines.
• Collaborates effectively across multidisciplinary teams spanning AI engineering, cloud security, identity, data, and risk management.

Requirements & Tech Stack

• Bachelor's degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field; alternatively, equivalent demonstrated experience.
• 2+ years of experience in cybersecurity, with demonstrated exposure to technology strategy engagements, risk assessments, and security architecture.
• Familiarity with established cybersecurity and AI governance frameworks such as NIST CSF, NIST AI RMF, ISO 42001, or the EU AI Act.
• Experience conducting or contributing to threat modeling, architecture risk assessments, or security gap analyses against defined control frameworks.
• Working knowledge of at least one major cloud platform (AWS, Azure, or Google Cloud), including an understanding of native security services, shared responsibility models, and cloud-native architecture patterns.
• Foundational understanding of AI and machine learning concepts, including how LLMs, RAG pipelines, vector databases, and agentic systems function, and the security risks they introduce.
• Ability to produce clear, structured technical documentation - including architecture diagrams, control mapping matrices, risk registers, and strategy decks - suitable for both engineering and executive audiences.
• Ability to travel 25% to 50%, on average, based on the work you do and the clients and engagements you serve.

Preferred Qualifications

• Previous consulting, client delivery, or customer-facing engineering experience.
• Experience across both managed AI services, self-hosted, and other AI platforms.
• Excellent communication (verbal and written) and interpersonal skills.
• Hands-on experience developing AI cybersecurity assessments, AI threat modeling, and AI policies and standards development.
• Experience with AI frameworks and regulations including NIST AI RMF, EU AI Act, and ISO 42001.
• Relevant certifications such as CISSP, CRISC, etc.