AI Datacenter Associate VP
- 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.
- 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.
- 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.
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