Senior Manager, Product Software Engineering - Foundations Engineering

The Walt Disney Company • Glendale, CA

4d • $188,400 - $276,700 • Hybrid

About The Position

Disney Entertainment and ESPN Product & Technology is seeking a Senior Manager, Product Software Engineering - Foundations Engineering. This role will lead the day-to-day engineering execution, operational reliability, and platform delivery of the Foundations Engineering function within Ad Platforms. The team is responsible for the internal capability layer that powers every service, application, and system in the organization. This includes leadership across platform engineering and DevOps, cloud infrastructure and runtime operations, SRE and reliability practices, database administration, observability enablement, and the infrastructure and platform capabilities supporting the Data Platform, BI ecosystem, and AI agentic and real-time ML platform. The role requires a leader who is deeply execution-oriented and operationally excellent, thrives on building reliable, scalable systems, leading high-performing engineering teams, and improving platform quality and developer experience. The position reports to the Director, Product Software Engineering - AI Engineering + Foundations Engineering.

Requirements

• 10+ years of software engineering experience, with demonstrated depth in platform engineering, cloud infrastructure, DevOps, SRE, or related foundations disciplines.
• Proven people management experience leading engineering teams - hiring, coaching, performance management, and building engineering delivery culture within a platform or infrastructure organization.
• Strong cloud infrastructure and platform engineering expertise - AWS required (hands-on operational depth); Azure and GCP experience valued; Kubernetes and container orchestration, Infrastructure-as-Code, and CI/CD platform operations at production scale.
• Demonstrated reliability engineering experience - SLO/SLI design, incident management, production readiness practices, and observability across high-availability, distributed systems.
• Database engineering and operational data infrastructure experience - managing relational and cloud-native databases at production scale, with exposure to data platform infrastructure (lakehouse, streaming, or orchestration systems) a strong plus.
• Familiarity with AI infrastructure and ML platform operations - inference runtimes, agent orchestration infrastructure, GPU/compute platform management, or operational AI platform support sufficient to lead effective teams in these domains.
• FinOps and cost management discipline - tracking cloud spend, driving capacity efficiency, eliminating waste, and communicating cost tradeoffs clearly.
• Strong cross-team collaboration and communication skills - able to coordinate effectively with AI Engineering, Product Engineering, Security, Data, Finance, and centralized Platform Engineering teams, and to represent Foundations Engineering planning and progress to senior stakeholders.
• Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.

Nice To Haves

• Experience in online advertising technology - familiarity with ad serving systems, programmatic platforms, campaign management, or streaming ad delivery infrastructure.
• Experience building or contributing to an internal developer platform (IDP) - self-service engineering tooling, golden-path frameworks, platform abstractions, or developer experience improvements at scale.
• Familiarity with Databricks, Snowflake, Apache Kafka, or similar cloud-native data platform technologies used in lakehouse or real-time streaming infrastructure.
• Experience with AI/ML runtime infrastructure - vector databases, embedding pipelines, model serving, inference systems, or agent execution platforms.
• Background in high-availability, high-scale real-time systems - live streaming, live advertising, event-driven architectures, or real-time bidding - operating across multi-cloud environments.
• Demonstrated practice in automation-first operational models - reducing operational toil through tooling, scripting, platform engineering, and infrastructure automation rather than manual processes.

Responsibilities

• Manages and delivers the platform engineering and DevOps capabilities that power software delivery across Ad Platforms, including CI/CD systems, Kubernetes, Infrastructure-as-Code, deployment automation, cloud platform integrations (AWS, Azure, GCP), and internal developer tooling.
• Drives automation-first operational practices, golden-path engineering patterns, self-service engineering capabilities, and Ads-specific platform abstractions to accelerate engineering velocity and reduce operational toil.
• Serves as a primary operational ownership layer for Ad Platforms workloads running on shared infrastructure, partnering with centralized Platform Engineering organizations.
• Implements and enforces secure-by-default platform standards, including secrets management, deployment governance, quality gates, vulnerability remediation, auditability, and compliance controls.
• Develops internal developer tooling and web-based operational interfaces to support service deployment, runtime management, and engineering productivity.
• Establishes and operates reliability engineering practices, including SLO/SLI frameworks, incident management, production readiness standards, and resiliency engineering.
• Leads observability operations and enablement, including logging, monitoring, distributed tracing, and alerting frameworks.
• Leads database engineering operations and data infrastructure enablement, including reliability, backup and recovery, performance optimization, and modernization efforts.
• Builds and operates infrastructure and platform capabilities supporting AI agentic and real-time ML systems, including orchestration runtimes, inference platform enablement, and GPU/compute orchestration.
• Executes FinOps and cost management practices across multi-cloud infrastructure and AI inference workloads, including capacity planning, cloud spend visibility, and utilization optimization.
• Leverages observability signals and automation to drive anomaly detection, incident prevention, and intelligent alerting.
• Leads, develops, and grows a high-performing engineering organization across Foundations Engineering's platform domains.
• Owns delivery execution and roadmap commitments across Foundations Engineering domains, planning quarterly work, coordinating dependencies, and leading postmortems and operational reviews.

Benefits

• A bonus and/or long-term incentive units may be provided as part of the compensation package
• full range of medical, financial, and/or other benefits, dependent on the level and position offered

What This Job Offers

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