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AI Datacenter & Infrastructure Associate VP

Join our AI & Engineering team and help transform technology platforms, drive innovation, and make a significant impact on our clients' success. You'll collaborate with talented professionals, reimagining and re-engineering operations and processes that are critical to business, and translating the physical constraints now shaping AI infrastructure into the hybrid cloud, orchestration, and managed services solutions clients need. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through infrastructure built for AI at scale.

AI & Engineering leverages innovative engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead of AI infrastructure's fastest-moving constraints by transforming engineering teams, modernizing technology and data platforms, and integrating closely with the partner ecosystem that owns the physical layer. Our delivery models are tailored to meet each client's unique requirements.

Recruiting for this role ends on 12/31/2026.

Work you'll do

• Drive the strategy and delivery of AI-centric datacenter transformations: lead the end-to-end planning, design, and execution of complex hybrid infrastructure projects, aligning with clients' business and AI objectives.
• Shape client solutions and build trusted relationships with architects and executives: serve as a strategic advisor to C-suite and senior IT leaders, translating business needs into infrastructure solutions that enable advanced AI capabilities. Bring fluency in how upstream power and cooling constraints shape the orchestration and operations decisions this team owns.
• Oversee multi-disciplinary project teams: direct and mentor diverse teams, ensuring seamless collaboration across infrastructure, AI, cloud, and cybersecurity domains, and coordinating cleanly with alliance partners who own power, cooling, and facility engineering scopes.
• Build and grow the AI Datacenter practice & capabilities: lead the growth, strategy, and talent development of the practice by shaping service offerings, driving innovation, expanding client relationships. Build teams fluent enough in AI infrastructure physics to scope engagements accurately and hand off cleanly to alliance partners where appropriate.
• Advance thought leadership and market presence: represent the firm at industry events, contribute to go-to-market strategies, and drive development of reusable assets that showcase expertise in AI datacenter solutions, including how power and cooling realities inform infrastructure and managed services design.
• Ensure high-quality project delivery and client satisfaction: take accountability for meeting project milestones, managing budgets, and maintaining strong client relationships through proactive communication and solution-oriented problem solving.
• Promote continuous innovation: champion emerging technologies and best practices in AI, edge computing, and hybrid cloud, fostering a culture of learning and excellence within the team.

The Team

Our Hybrid Cloud Infrastructure offering delivers infrastructure engineering capabilities to design, implement, manage, and operate hybrid cloud environments. We modernize networks and AI infrastructure from the core to the edge and develop new infrastructure and device services to help clients stay ahead of the latest technology advancements, working alongside the partners who own the power and physical layer.

Qualifications

Required

• 10+ years of experience modernizing and adapting datacenter environments to align with clients' specific requirements, enabling successful execution of tailored AI strategies.
• 5+ years of experience designing architectures that span on-prem, colocation, and hyperscaler environments; experience with containerized AI workloads (Kubernetes, Kubeflow), data fabric patterns, and edge inference deployment strategies. 
• 10+ years of experience architecting, implementing, and optimizing enterprise-scale hybrid infrastructure solutions (GPU platforms, server hardware, AI transformation), including working fluency in how rack power density and liquid cooling requirements shape infrastructure and capacity planning decisions.
• 7+ years of experience designing, delivering, and supporting hybrid cloud and as-a-Service solutions, integrating ease-of-use features for end-users, onboarding via ITSM tools (ServiceNow), and ensuring compliance with enterprise security and governance standards.
• 3+ years of experience implementing infrastructure as code (Terraform, Ansible), AIOps for predictive maintenance, DCIM modernization, and automation pipelines for provisioning and monitoring GPU clusters.
• 10+ years of experience in project management, including planning, organizing, and delivering complex infrastructure projects on time and under budget; skilled at managing cross-functional teams, setting clear objectives, and mitigating risks to ensure project success.
• 12+ years of relevant consulting or industry experience and large scale, enterprise class consulting or systems integration experience.
• Bachelor's Degree or equivalent experience.
• Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

• Working fluency in AI/ML workload characteristics (training vs. inference), GPU/TPU architectures, high-performance interconnects (InfiniBand, NVLink), and current cooling and power realities (direct-to-chip and immersion liquid cooling, megawatt-scale rack power, grid and energy constraints) - enough to advise clients and integrate credibly with alliance partners who deliver that layer, not to execute it directly.
• Strong financial modeling skills for TCO/ROI, capacity planning for AI workloads, and applying ESG principles (e.g., PUE optimization, tokens-per-watt, carbon-aware computing) to infrastructure investments.
• Proven ability to lead cross-functional teams delivering AI-ready data center transformations; adept at executive storytelling, client relationship development, and managing multi-million-dollar transformation portfolios.
• Understanding of hyperscaler services (AWS Bedrock, Azure AI, GCP Vertex AI), colocation and interconnect providers, and hardware ecosystems (NVIDIA DGX, Dell, HPE, Supermicro). Able to architect vendor-neutral and partnership-driven client strategies.
• Ability to make and meet commitments on a tight timeline with right-sized scoping on "must haves" to realize customer wins.
• High executive presence and presentation skills with a high degree of comfort with both large and small audiences, with varying degrees of technical depth, including the ability to translate physical-layer constraints (power, cooling) into terms relevant to the orchestration and managed services layers HCI owns.
• Experience collaborating with cross-functional teams (Sales, Marketing, Product) to develop and execute market expansion strategies.
• Proven ability to collaborate with Data Scientists and ML Engineers to understand infrastructure needs and deliver robust, scalable solutions.

Wages + Salary

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 $171,600 to $338,300. 

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.

AI Datacenter & Infrastructure Associate VP

Join our AI & Engineering team and help transform technology platforms, drive innovation, and make a significant impact on our clients' success. You'll collaborate with talented professionals, reimagining and re-engineering operations and processes that are critical to business, and translating the physical constraints now shaping AI infrastructure into the hybrid cloud, orchestration, and managed services solutions clients need. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through infrastructure built for AI at scale.

AI & Engineering leverages innovative engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead of AI infrastructure's fastest-moving constraints by transforming engineering teams, modernizing technology and data platforms, and integrating closely with the partner ecosystem that owns the physical layer. Our delivery models are tailored to meet each client's unique requirements.

Recruiting for this role ends on 12/31/2026.

Work you'll do

• Drive the strategy and delivery of AI-centric datacenter transformations: lead the end-to-end planning, design, and execution of complex hybrid infrastructure projects, aligning with clients' business and AI objectives.
• Shape client solutions and build trusted relationships with architects and executives: serve as a strategic advisor to C-suite and senior IT leaders, translating business needs into infrastructure solutions that enable advanced AI capabilities. Bring fluency in how upstream power and cooling constraints shape the orchestration and operations decisions this team owns.
• Oversee multi-disciplinary project teams: direct and mentor diverse teams, ensuring seamless collaboration across infrastructure, AI, cloud, and cybersecurity domains, and coordinating cleanly with alliance partners who own power, cooling, and facility engineering scopes.
• Build and grow the AI Datacenter practice & capabilities: lead the growth, strategy, and talent development of the practice by shaping service offerings, driving innovation, expanding client relationships. Build teams fluent enough in AI infrastructure physics to scope engagements accurately and hand off cleanly to alliance partners where appropriate.
• Advance thought leadership and market presence: represent the firm at industry events, contribute to go-to-market strategies, and drive development of reusable assets that showcase expertise in AI datacenter solutions, including how power and cooling realities inform infrastructure and managed services design.
• Ensure high-quality project delivery and client satisfaction: take accountability for meeting project milestones, managing budgets, and maintaining strong client relationships through proactive communication and solution-oriented problem solving.
• Promote continuous innovation: champion emerging technologies and best practices in AI, edge computing, and hybrid cloud, fostering a culture of learning and excellence within the team.

The Team

Our Hybrid Cloud Infrastructure offering delivers infrastructure engineering capabilities to design, implement, manage, and operate hybrid cloud environments. We modernize networks and AI infrastructure from the core to the edge and develop new infrastructure and device services to help clients stay ahead of the latest technology advancements, working alongside the partners who own the power and physical layer.

Qualifications

Required

• 10+ years of experience modernizing and adapting datacenter environments to align with clients' specific requirements, enabling successful execution of tailored AI strategies.
• 5+ years of experience designing architectures that span on-prem, colocation, and hyperscaler environments; experience with containerized AI workloads (Kubernetes, Kubeflow), data fabric patterns, and edge inference deployment strategies. 
• 10+ years of experience architecting, implementing, and optimizing enterprise-scale hybrid infrastructure solutions (GPU platforms, server hardware, AI transformation), including working fluency in how rack power density and liquid cooling requirements shape infrastructure and capacity planning decisions.
• 7+ years of experience designing, delivering, and supporting hybrid cloud and as-a-Service solutions, integrating ease-of-use features for end-users, onboarding via ITSM tools (ServiceNow), and ensuring compliance with enterprise security and governance standards.
• 3+ years of experience implementing infrastructure as code (Terraform, Ansible), AIOps for predictive maintenance, DCIM modernization, and automation pipelines for provisioning and monitoring GPU clusters.
• 10+ years of experience in project management, including planning, organizing, and delivering complex infrastructure projects on time and under budget; skilled at managing cross-functional teams, setting clear objectives, and mitigating risks to ensure project success.
• 12+ years of relevant consulting or industry experience and large scale, enterprise class consulting or systems integration experience.
• Bachelor's Degree or equivalent experience.
• Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
• Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred

• Working fluency in AI/ML workload characteristics (training vs. inference), GPU/TPU architectures, high-performance interconnects (InfiniBand, NVLink), and current cooling and power realities (direct-to-chip and i...