US E - Consulting Services - Cyber Digital Trust & Privacy - Cyber for AI - Sr Consultant: Infrastructure Security

As a AI Infrastructure Senior Consultant in our Cyber for AI team, you will lead technical workstreams that secure how artificial intelligence (AI) agents, workloads, and users authenticate, receive permissions, and access enterprise tools and data. You will combine client advisory and hands-on engineering to translate requirements into architecture, integration, and production controls. You will guide junior practitioners, lead demonstrations, and help estimate delivery work. Recruiting for this role ends on 05/31/2027. Work you'll do As an AI Infrastructure Senior Consultant on the Infrastructure team, you will be responsible for: Owning an infrastructure workstream, managing dependencies and milestones, providing day-to-day guidance to consultants, and contributing technical demonstrations, prototypes, architecture, effort, and estimation inputs to pursuits. Leading discovery and architecture analysis for managed AI services, self-hosted model stacks, cloud foundations, networks, and operational tooling. Designing and deploying secure AI landing zones and model-serving environments across AWS, Azure, Google Cloud, or Kubernetes-based platforms. Leading implementation of network isolation, private access, egress controls, cluster security, secrets management, artifact controls, infrastructure as code (IaC), and policy enforcement. Engineering and reviewing Kubernetes and model-serving patterns for tenant isolation, GPU workloads, autoscaling, resilience, and controlled enterprise integration. Planning and executing platform security, resilience, and operational testing. Diagnosing complex failures and driving issues through resolution. The Team Deloitte's Cyber for AI team helps organizations secure generative AI and agentic systems from design through production. 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. Infrastructure capability in our team focuses on secure AI landing zones, cloud and network architecture, container and model-serving platforms, policy automation, and observability. Qualifications 3-5+ years of combined cybersecurity and AI engineering experience, including hands-on production work in both domains and experience designing, integrating, and securing production generative AI, retrieval-augmented generation (RAG), or agentic workloads, including model, tool, and enterprise data connections. Required: Hands-on experience designing and securing cloud, network, Kubernetes, container, and model-serving platforms in AWS, Azure, or Google Cloud, including secure AI landing zones. Experience implementing network segmentation, private connectivity, egress controls, Domain Name System (DNS), Transport Layer Security (TLS), firewalls, gateways, service meshes, and enterprise integration patterns. Experience implementing or reviewing infrastructure automation, Kubernetes configurations, deployment pipelines, and operational diagnostics using Terraform, AWS CloudFormation, or Azure Bicep. Experience in CI/CD pipelines, policy-as-code, Kubernetes role-based access control (RBAC), network policies, admission controls, and secrets management. Programming capabilities with Python, Go, Bash, PowerShell, HashiCorp Configuration Language (HCL) and/or YAML and Git. 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 in consulting, client delivery, or customer-facing engineering, including developing reusable technical assets, guiding junior engineers, or contributing to engineering standards. Experience across both managed AI services and self-hosted or open-weight AI platforms. Experience with AI threat modeling, red teaming, security evaluations, secure AI development practices, or AI-specific monitoring. Experience using PyTorch, TensorFlow, or MLflow for machine learning development, deployment, or monitoring. Experience with 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. Experience securing 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) and/or 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 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. A reasonable estimate of the current range is $105,400 to $207,800. 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. 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. #LI-DT6