Cyber Manager: AI Security - Infrastructure

As a Cyber for AI: Manager, Infrastructure in Deloitte's Cyber for AI team, you will lead client engagements that secure the cloud, network, container, and model-serving foundations used for generative artificial intelligence (AI) and agentic workloads. You will translate business and risk objectives into target architectures, remain involved in design and engineering decisions, and guide teams from assessment through implementation. You will also shape solutions during pursuits and help build repeatable delivery assets.

Recruiting for this role ends on 05/31/2027.

Work You'll Do

As a Cyber for AI: Manager, Infrastructure on the Infrastructure team, you will be responsible for:

• Leading secure AI landing-zone assessments, architecture workshops, and implementation programs across cloud, network, Kubernetes, and model-serving platforms.
• Translating workload, risk, performance, and operational requirements into target architectures for managed and self-hosted AI environments.
• Providing hands-on technical oversight through design reviews, infrastructure as code (IaC) and policy decisions, configuration and code reviews, and resolution of technical issues.
• Managing engagement scope, teams, milestones, quality, and client expectations.
• Coordinating dependencies across AI engineering, identity, data, application security, DevSecOps, and operations teams.
• Shaping solutions during pursuits through workshops, demonstrations, proofs of concept, estimates, and delivery plans; develop reusable landing-zone blueprints, automation, and delivery methods
• Coaching practitioners on engineering quality.

The Team

Deloitte's Cyber for AI team helps organizations secure generative AI and agentic systems from design through production. Within the practice, the Infrastructure capability focuses on secure AI landing zones, cloud and network architecture, container and model-serving platforms, policy automation, and observability.

The team combines AI engineering and cyber capabilities across identity, data, infrastructure, application security, and operations. We work with clients to integrate security controls into the platform and delivery lifecycle so teams can move from experiments to production while managing access, data, and infrastructure risks.

Qualifications

6+ years of combined cybersecurity and AI engineering experience, including hands-on production work in both domains and experience architecting and leading production generative AI or agentic implementations, including technical decisions involving models, orchestration, identity, data, and infrastructure.

Required Experience:

• Architecting and implementing secure AI landing zones across AWS, Azure, and/or Google Cloud environments including network, Kubernetes, container, and model-serving platforms.
• Security infrastructure including private connectivity, segmentation, egress control, gateways, service meshes, secrets, encryption, and operational telemetry.
• Implementing Infrastructure as Code (IaC), CI/CD, and policy-as-code using Terraform, CloudFormation, Bicep, Open Policy Agent, Gatekeeper, Kyverno, or comparable tools.
• Kubernetes configuration, deployment pipelines, and operational diagnostics.
• Leading client-facing technology or cyber engagements including scope, team management, delivery timelines, and quality management.
• Coordinating across AI Engineering, Identity, Data, Application Security, and DevSecOps teams.
• Bachelor's degree in Computer Science, Engineering, Information Technology, Cybersecurity or a related field.
• Ability to travel 20% to 50%, on average, based on the work you do and the clients and industries/sectors you serve.
• Limited immigration sponsorship may be available.

Preferred Experience:

• Managed AI services and self-hosted or open-weight AI platforms.
• AI threat modeling, red teaming, security evaluations, secure AI development practices, or AI-specific monitoring.
• Building reusable technical assets, delivery methods, or automation for client engagements.
• Machine learning tools and frameworks such as PyTorch, TensorFlow, or MLflow.
• AI platforms and model-serving technologies such as Amazon Bedrock/Bedrock AgentCore, SageMaker AI, Microsoft Foundry, Azure Machine Learning, Google Vertex AI, vLLM, KServe, NVIDIA Triton, NVIDIA Inference Microservices (NIM), or Ray Serve.
• Securing graphics processing unit (GPU) infrastructure, model and container registries, software supply chains, signed artifacts, service meshes, or multi-tenant inference environments.

Certifications Preferred:

• Certified Information Systems Security Professional (CISSP)
• Certified Cloud Security Professional (CCSP)
• Certified Kubernetes Administrator (CKA) / Security Specialist (CKS)
• AWS / Azure / GCP Cloud certifications
• Certified Terraform Associate / Infrastructure Engineer Professional

A successful candidate would possess these skills:

• Ability to work independently and collaborate as part of a team
• Effective written and verbal communication skills
• Meticulous attention to detail and quality of work product
• Ability to build and sustain professional relationships
• Ability to lead projects or workstreams
• Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
• Strong interpersonal skills and professional demeanor
• Ability to meet deadlines
• Ability to mentor and provide clear guidance to others

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $134,500 to $265,100.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.