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, an...