Cyber- DT&P-Strategy & Architecture - AI Security Senior Consultant

AI Security Consultant, Strategy and Architecture
As a Senior Consultant in our AI Cyber Strategy & Architecture practice, you will take a leading role in designing and delivering enterprise-grade AI security frameworks, reference architectures, and AI governance programs for our clients. You will work with independence and technical authority, driving the execution of complex engagements while mentoring junior team members and beginning to shape client relationships. This role sits at the intersection of AI innovation and cybersecurity risk - translating sophisticated threat landscapes into actionable, business-aligned security strategies.
You will be expected to bring a depth of expertise across AI security architecture, threat modeling, and compliance alignment, while demonstrating the ability to lead workstreams end-to-end with minimal supervision.
Work you'll do
As an AI Cyber Strategy and Architecture Senior Consultant, you will be responsible for:
Lead discovery sessions to translate regulatory and framework requirements - including NIST AI RMF, EU AI Act and ISO 42001- 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.
A successful candidate would possess these 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.
The team
Deloitte Cyber for AI practice helps organizations secure generative AI and agentic systems from design through production. The team brings together AI engineering and cyber skills across identity, data, infrastructure, application security and operations.
We work with clients to make security controls part of the platform and delivery lifecycle, so teams can move from experiments to production without creating unmanaged access, data or infrastructure risk.
Within the practice, the Identity capability focuses on how agents, workloads and people are identified, authenticated, authorized and governed across enterprise and cloud environments.
Qualifications
Required:
Bachelor's degree in Computer Science, Engineering, Information Technology, Cybersecurity, or a related field; alternatively, equivalent demonstrated experience.
4+ 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:
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 cyber security assessments, AI threat modelling 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
.
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