AI Platform Engineering Lead (Senior Manager)

EY • Hartford, DC

3d • $144,000 - $374,000

About The Position

EY is seeking a senior player-coach to lead its AI Platform Engineering group, which builds and operates the foundational infrastructure and cloud-native platform for EY’s AI runtime. The role sets technical direction for AI Infrastructure and AI Systems Engineers and is accountable for delivering and operating AI environments across cloud, on-premises, edge, client-managed, and air-gapped targets. The leader directs the team and owns its delivery roadmap while remaining hands-on with the design, implementation, and troubleshooting of the platform’s most critical components.

The position owns the platform foundation from operating systems, bare metal, GPU and DPU infrastructure through Kubernetes, scheduling, networking, multi-tenancy, distributed compute, secure execution, inference, and routing. It is responsible for providing a production-ready, modular, and portable substrate for Agentic AI workflows, with consistent stack contracts across deployment environments and components that can be replaced without rewriting consumers.

The role also owns operational reliability and resilience, including SLOs, on-call and incident practices, disaster recovery, backups, replication, patching, security hardening, and supply-chain hygiene. It partners with DevOps Engineers on CI/CD, infrastructure-as-code, and GitOps, and manages GPU capacity, quotas, cost attribution, budgets, vendor evaluations, procurement, and capacity planning. The position communicates delivery progress, risks, trade-offs, and resource needs to senior leadership and other stakeholders.

Requirements

• Bachelor’s or Master’s degree in Computer Science or a related technical field.
• At least 10 years building or operating enterprise infrastructure, cloud platforms, or large-scale Kubernetes environments, including deep, current hands-on systems expertise.
• At least 3 years leading or directing engineering teams, while remaining an active hands-on contributor.
• Track record owning a platform or infrastructure roadmap and architecture end to end, from requirements and estimation through phased delivery and steady-state operations.
• Hands-on expertise with Kubernetes distributions including RKE2, EKS, AKS, GKE, or K3s, and production-scale cluster lifecycle management.
• Deep experience with bare-metal, cloud, hybrid, and on-premises deployment models; air-gapped deployment experience is also cited as a qualification.
• Strong grounding in cluster networking, including Cilium, service mesh, or CNI, as well as storage and multi-tenancy isolation.
• Hands-on experience with GPU infrastructure and scheduling, including NVAIE/DCGM, GPU operators, virtualization/MIG, and AI inference serving such as vLLM, NIM, Triton, or Ray Serve.
• Experience with infrastructure-as-code and GitOps tooling such as Terraform/OpenTofu, Helm, ArgoCD, or Crossplane.
• Experience with disaster recovery, backup, and cross-environment replication tiered by RPO/RTO.
• Track record operating production infrastructure under compliance, security, or regulatory constraints, including incident leadership and SLO ownership.
• Experience managing infrastructure budgets, capacity plans, and vendor relationships.
• Ability to work effectively with security, architecture, product, and delivery teams and defend technical decisions to senior stakeholders.

Nice To Haves

• Experience leading an AI/ML or GPU-intensive platform build from early stage to production, including GPU virtualization, MIG, or AI workload scheduling.
• Experience with multi-tenant platforms and tenancy isolation at scale, such as vCluster.
• Familiarity with distributed compute and batch orchestration, including Kueue, Slurm/Slinky, Ray, or OpenMPI.
• Experience with sandboxed and confidential execution technologies such as gVisor, Firecracker, or confidential computing.
• Background in platform or SRE leadership measured by downstream team velocity, reliability, and portability.
• Exposure to regulated delivery environments such as financial services, tax, healthcare, or risk.
• Relevant certifications such as CKA/CKS, NVIDIA AI Infrastructure, or AWS, Azure, or GCP professional-level certifications.

Responsibilities

• Lead, prioritize, and develop AI Infrastructure and AI Systems Engineers; hire, mentor, coach, set engineering standards, allocate work, and remove blockers.
• Personally design, implement, and debug high-risk platform components, including cluster bring-up, GPU and networking enablement, multi-tenancy, inference, and routing.
• Own and sequence the infrastructure delivery roadmap into usable phases, define delivery gates, and report progress, risks, and trade-offs to senior leadership.
• Own the infrastructure foundation and cloud-native platform, including operating systems, bare-metal and DPU architecture, GPU infrastructure, Kubernetes and scheduling, cluster networking, multi-tenancy, and distributed compute.
• Stand up and operate Agentic AI environments across cloud, on-premises AI Factory, edge, client-managed, and air-gapped deployments while maintaining a consistent, modular, portable stack.
• Own secure execution, inference, and routing capabilities, including sandboxed execution, inference serving, AI gateways, semantic routing, model and prompt selection, and streaming responses.
• Define SLOs, on-call and incident-management practices, and lead post-incident reviews.
• Own backup, disaster recovery, cross-environment replication, patching, security hardening, and supply-chain hygiene.
• Partner with DevOps Engineers on CI/CD, infrastructure-as-code, and GitOps to make environments reproducible and drift-free.
• Forecast GPU capacity, set quotas and cost attribution, manage infrastructure budgets, evaluate vendors and technologies, run proofs of concept, manage vendor relationships, and coordinate procurement for hardware and licensing.

Benefits

• Medical and dental coverage.
• Pension and 401(k) plans.
• Flexible vacation policy.
• Paid holidays.
• Winter and summer breaks.
• Personal and family care time off.
• Other leaves of absence to support physical, financial, and emotional well-being.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior