Job Posting Title:
Senior Manager, Product Software Engineering - Foundations Engineering
Req ID:
Job Description:
Job Summary The Sr. Manager, Foundations Engineering leads the day-to-day engineering execution, operational reliability, and platform delivery of the Foundations Engineering function within Ad Platforms - the internal capability layer that powers every service, application, and system in the organization. The organization owns and operates portions of the Ad Platforms infrastructure and developer platform stack directly, while also extending, operationalizing, and supporting shared enterprise platforms within the Ad Platforms ecosystem.
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. This role partners closely with centralized Platform Engineering and Infrastructure teams responsible for shared enterprise services and cloud platforms. This role reports to the Director, Product Software Engineering - AI Engineering + Foundations Engineering.
We are seeking a Sr. Manager who is deeply execution-oriented and operationally excellent - someone who thrives on building reliable, scalable systems, leading high-performing engineering teams through delivery, and improving platform quality and developer experience quarter over quarter. If you are a leader who takes pride in production stability, drives operational discipline without creating bureaucracy, and knows how to develop engineers while keeping the platforms running at scale, this is an exceptional opportunity.
Responsibilities and Duties of the Role: Platform Engineering & DevOps- Manages and delivers the platform engineering and DevOps capabilities that power software delivery across Ad Platforms - including ownership and operational support of CI/CD systems, Kubernetes and container orchestration environments, Infrastructure-as-Code modules, deployment automation, shared cloud platform integrations across AWS (primary), Azure, and GCP, and internal developer tooling - improving deployment speed, reliability, scalability, and developer experience.
- Drives automation-first operational practices, golden-path engineering patterns, self-service engineering capabilities, and Ads-specific platform abstractions built on top of shared infrastructure platforms - accelerating engineering velocity, reducing operational toil, and improving onboarding, deployment reliability, and release consistency across Ad Platforms teams.
- Serves as a primary operational ownership layer for Ad Platforms workloads running on shared infrastructure and platform services - partnering closely with centralized Platform Engineering organizations responsible for core cloud, Kubernetes, CI/CD, and observability platforms.
- Implements and enforces secure-by-default platform standards across Ad Platforms environments and delivery pipelines - including secrets management, deployment governance, engineering quality gates, vulnerability remediation, auditability, and compliance controls - in partnership with Security and centralized infrastructure teams.
- Develops internal developer tooling and web-based operational interfaces that support service deployment, runtime management, and engineering productivity across Ad Platforms.
Reliability, Data & AI Platform Infrastructure- Establishes and operates reliability engineering practices across Ad Platforms foundational services and runtime environments - including SLO/SLI frameworks, incident management rigor, production readiness standards, operational health monitoring, and resiliency engineering practices - driving measurable improvements in uptime, stability, and deployment confidence.
- Leads observability operations and enablement across Ad Platforms - including logging, monitoring, distributed tracing, alerting frameworks, and operational instrumentation standards - partnering with centralized observability teams to ensure consistent and actionable visibility into system behavior and platform health.
- Leads database engineering operations and data infrastructure enablement for Ad Platforms, including operational reliability, backup and recovery strategy, failover readiness, performance optimization, and modernization efforts across relational, NoSQL, and cloud-native data systems supporting transactional services, analytics, BI, and Data Platform workloads.
- Builds and operates infrastructure and platform capabilities supporting AI agentic and real-time ML systems - including orchestration runtimes, inference platform enablement, GPU and compute orchestration, deployment automation, and governance-aligned operational frameworks - enabling AI Engineering teams to develop, deploy, and scale AI systems reliably and safely.
- Executes FinOps and cost management practices across multi-cloud infrastructure and AI inference workloads - including capacity planning, cloud spend visibility, utilization optimization, waste reduction, and unit cost reporting - contributing to engineering efficiency and responsible resource utilization.
- Leverages observability signals and automation to drive anomaly detection, incident prevention, and intelligent alerting across Ad Platforms services and platforms.
Team Leadership & Delivery- Leads, develops, and grows a high-performing engineering organization across Foundations Engineering's platform domains - managing engineers and technical leads directly, driving hiring and performance management, establishing execution cadence, and fostering a culture of operational excellence, accountability, continuous improvement, and engineering craft.
- Owns delivery execution and roadmap commitments across Foundations Engineering domains - planning quarterly work, coordinating dependencies with AI Engineering, Product Engineering, Security, Data, and centralized Platform teams, leading postmortems and operational reviews, and continuously improving delivery predictability, production quality, and platform health.
Required Education, Experience/Skills/Training:- 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.
Preferred Qualifications - 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.
Required Education - Bachelor's degree in Computer Science, Engineering, or a related field; advanced degree preferred.
Location- Hybrid role: 4+ days/week in office - Glendale, CA or San Francisco, CA
#disneytech
The hiring range for this position in Los Angeles, CA is between $188,400 - $252,600 and San Francisco, CA is between $206,400 - $276,700. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.
Job Posting Segment:
Ad Platforms
Job Posting Primary Business:
AP - Engineering
Primary Job Posting Category:
Product Software Engineering
Employment Type:
Full time
Primary City, State, Region, Postal Code:
Glendale, CA, USA
Alternate City, State, Region, Postal Code:
USA - CA - Market St
Date Posted:
2026-09-03
