Director of Platform Engineering

Senior technical leadership role within Gen Digital's Production Operations organization, accountable for the platforms, infrastructure, and tooling that the development and technology organization builds on. The role leads the Cloud Platform, Productivity Platform, and AI Platform teams and their engineering managers, and is responsible for the availability, scalability, performance, cost efficiency, and compliance posture of the shared platform estate across AWS, Google Cloud, and Azure.

Responsibilities

Own the multi-year technical strategy and roadmap for the Cloud Platform, Productivity Platform, and AI Platform teams; Operate the platforms as products, publishing golden paths and paved roads and managing a prioritized backlog; Define and instrument platform value metrics and report them to executive stakeholders; Reduce cognitive load across engineering through abstraction, reusable templates, and opinionated defaults; Set standards for infrastructure as code, policy as code, service catalogs, and platform APIs; Lead multi-cloud infrastructure design, delivery, and operation across AWS, Google Cloud, and Azure; Drive Kubernetes and container platform strategy, progressive delivery, service mesh, secrets management, and zero-trust network patterns; Own cloud financial management (FinOps) for the platform estate; Own the engineering productivity and developer experience toolchain, including CI/CD, artifact management, and developer portal; Build and operate the shared AI platform, including model gateway, inference, retrieval services, and MLOps/LLMOps practice; Manage GPU and accelerator capacity, quota, and token consumption across clouds; Own production health of the platform estate, including 24x7 support, incident command, problem management, and postmortems; Define and defend SLOs, SLIs, and error budgets; Lead resilience engineering, including disaster recovery and chaos exercises; Lead and develop a multi-team organization of engineering managers, staff and principal engineers, and platform engineers; Manage budget, vendor relationships, and contract negotiation for platform and AI infrastructure spend; Represent platform strategy to executive stakeholders

Requirements

Bachelor's degree in Computer Science, Engineering, Management Information Systems, or equivalent practical experience; Minimum 12 years of experience in software engineering, infrastructure, or technology operations; Minimum 6 years of experience leading engineering teams, including at least 3 years leading managers or leading multiple teams simultaneously; Demonstrated experience building, operating, and scaling production cloud infrastructure in AWS, Google Cloud, and Azure in a medium or large enterprise, with depth in at least one and working fluency in the other two; Proven track record building an internal developer platform or shared platform capability adopted at scale, with measurable improvements to delivery velocity, reliability, or cost; Deep hands-on grounding in platform engineering practice: infrastructure as code, Kubernetes and container platforms, CI/CD at scale, observability, policy as code, and self-service developer tooling; Working knowledge of modern AI and machine learning infrastructure, including model serving and inference, retrieval-augmented generation, vector data stores, accelerator capacity management, evaluation frameworks, and AI governance and safety controls; Experience owning a 24x7 production environment, including incident command, SLO and error budget management, and driving systemic reliability improvement; Experience with cloud financial management and multi-million-dollar infrastructure budget ownership; Strong executive communication skills, with a demonstrated ability to build consensus, influence change across organizational boundaries, and drive results; Demonstrated passion for building and leading cohesive technical teams, developing leaders, and taking pride in helping individuals achieve their best; Willingness to participate in and lead escalation for a 24x7 on-call rotating support schedule for production systems

Nice to have

Advanced degree in a technical discipline; Experience standing up an AI or machine learning platform from early stage through broad enterprise adoption; Experience with agentic systems, tool and context protocols, and LLM application observability in production; Background in cybersecurity, financial services, or another regulated or real-time transaction processing industry; Experience operating under formal compliance regimes such as SOC 2, PCI DSS, ISO 27001, FedRAMP, or GDPR; Experience leading distributed or globally dispersed engineering organizations

Benefits

Flexible working options; Time off; Competitive pay; Benefits; Well-being programs