Oracle Cloud Infrastructure (OCI) is seeking a Director of Engineering to lead the NXI team within the Strategic Customer Engineering organization. The NXI team helps customers with new products, features, and regions. You will build and lead a team responsible for the technical success of some of OCI's largest AI infrastructure customers as they adopt new accelerator platforms, regions, and engineering capabilities.
Your team will guide customers from early platform evaluation through cluster validation, workload onboarding, production readiness, and expansion. The scope includes platforms such as GB200, GB300, MI355, MI450, Vera Rubin, and subsequent generations as introduced in OCI, together with new capabilities across compute, networking, storage, and cluster management.
You will work directly with customer engineering leaders and senior OCI stakeholders to turn customer requirements into tested solutions, resolve issues across the infrastructure stack, and ensure new products support customers' training and inference workloads at scale.
Internal Responsibilities
Build and lead an organization of engineering managers and senior customer and infrastructure engineers. Recruit technical talent, develop leaders, and establish clear accountability for customer outcomes.
Own technical onboarding from requirements discovery and architecture review through platform bring-up, workload migration, acceptance testing, production readiness, and expansion.
Agree measurable acceptance criteria with customers, including workload throughput, scaling efficiency, job completion, reliability, and time to first successful production workload.
Partner with OCI Compute, Networking, Storage, Product, Capacity, Operations, and Support teams, and technology suppliers, to resolve dependencies and align product readiness with customer deployment plans.
Serve as the senior technical escalation leader for the customer portfolio. Communicate impact, evidence, mitigation plans, and recovery milestones to customer and OCI executives.
Build automation, diagnostics, reference architectures, and onboarding playbooks that reduce manual effort and shorten time to production across platform generations.
12+ years of experience in software engineering, infrastructure engineering, or distributed systems, including delivery of cloud, AI, or high-performance computing infrastructure.
Technical depth in accelerated computing, Linux, high-performance networking, and distributed systems, with the ability to evaluate architecture, performance, and reliability tradeoffs.
Bachelor's or master's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
Knowledge of RDMA networking, accelerator interconnects, distributed training collectives, and storage performance for large AI workloads.
Experience partnering with AI model developers, large enterprise AI customers, hardware suppliers, or accelerator vendors.
Experience building software and automation for cluster qualification, health checks, diagnostics, or workload failure analysis.
