Engineering Manager

The Media Group at NBCU supports a powerhouse collection of consumer-first brands including Peacock, NBC, Bravo, NBC Sports, and NBCU International. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another. We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience.

But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive.

The Global Video Engineering organization is looking for an Engineering Manager to lead and develop our engineering team responsible for building the next generation of tooling, automation, data, and intelligence capabilities supporting video operations.

This role will lead a team of software engineers responsible for designing, building, and maintaining platforms used to operate, monitor, analyze, and improve NBCUniversal's video ecosystem across Live, Linear, and VOD experiences.

A key focus of this role will be the development of a centralized video intelligence and data platform that brings together operational, telemetry, scheduling, monitoring, and performance data from multiple systems. The platform will enable real-time visibility, correlation, advanced analytics, automation, and AI-driven operational capabilities.

The Engineering Manager will work closely with Product, Video Engineering, Operations, Architecture, Data Engineering, and other technology teams to establish scalable technical foundations while delivering high-value capabilities incrementally.

Roles & Responsibilities

• Build and lead an inclusive, high-performing engineering organization responsible for software platforms, data services, APIs, integrations, automation, and operational tooling.
• Provide technical leadership and architectural direction for a centralized video intelligence platform integrating data across multiple systems and domains.
• Lead engineers responsible for designing and developing scalable systems capable of ingesting, processing, normalizing, correlating, storing, and serving high-volume operational and telemetry data.
• Partner with senior engineers and architects to define the architecture for real-time and historical data processing, including streaming pipelines, event-driven architectures, APIs, data lake technologies, and analytical services.
• Establish engineering patterns for integrating disparate data sources while maintaining data quality, consistency, lineage, governance, and observability.
• Guide the development of a canonical/common data model that enables information from different video systems and platforms to be correlated and consumed consistently.
• Oversee the development of intelligence capabilities including anomaly detection, event correlation, intelligent alerting, automated triage, root-cause analysis, and predictive insights.
• Establish the technical foundation required to safely leverage machine learning, large language models, AI agents, and other emerging AI capabilities against operational video data.
• Partner with Product and Operations teams to translate operational problems and business requirements into scalable technical capabilities and engineering roadmaps.
• Work collaboratively across Video Engineering, Playback, Live/Linear, VOD, Operations, Architecture, Data Engineering, Cloud Infrastructure, and other technology organizations.
• Evaluate existing systems and workflows to identify opportunities for consolidation, automation, modernization, and improved interoperability.
• Drive architectural decisions related to scalability, resiliency, availability, latency, performance, security, and cost.
• Ensure systems are designed with appropriate observability, monitoring, logging, telemetry, and operational support capabilities.
• Establish and maintain strong API and integration standards to enable internal systems and applications to reliably contribute to and consume platform data.
• Drive engineering best practices across software design, code quality, automated testing, CI/CD, documentation, deployment, and operational readiness.
• Ensure solutions are properly unit tested, integration tested, performance tested and validated prior to production deployment.
• Lead technical design reviews and ensure architecture and engineering decisions are appropriately documented.
• Deliver against product and engineering roadmaps incrementally while balancing technical debt, platform investment, operational priorities, and business value.
• Partner with engineering teams to establish highly resilient and scalable architectures capable of supporting mission-critical video operations.
• Continuously identify opportunities to improve platform reliability, engineering efficiency, system performance, and developer experience.
• Grow the engineering team by attracting and retaining strong technical talent capable of operating across software, data, platform, and video engineering disciplines.
• Coach and develop engineers through regular 1:1s, technical mentorship, career development, continuous feedback, and clear expectations.
• Create an engineering culture that values ownership, collaboration, experimentation, documentation, technical excellence, and continuous improvement.

Desired Technical Experience

• 10+ years of software engineering experience, including experience operating at a senior or technical leadership level.
• Experience leading or managing software engineering teams responsible for complex, production-scale systems.
• Strong understanding of modern software and distributed systems architecture, including microservices, APIs, event-driven systems, and cloud-native application design.
• Experience designing or operating data platforms, data lakes, or large-scale analytical systems .
• Strong understanding of data ingestion and transformation patterns , including ETL/ELT, batch processing, real-time streaming, and event-driven architectures.
• Experience with technologies such as Kafka or equivalent event streaming platforms , as well as modern analytical or high-performance data stores.
• Experience designing systems capable of handling high-volume telemetry, time-series, event, and operational data .
• Strong understanding of API architecture, including RESTful services, service-to-service integrations, authentication, versioning, and API lifecycle management.
• Experience with cloud platforms and cloud-native architectures, including compute, storage, networking, containers, orchestration, and managed data services.
• Experience with modern software development languages and frameworks. Experience with technologies such as Go, Python, Java, JavaScript/TypeScript, React, or equivalent technologies is beneficial.
• Understanding of data architecture concepts including schema design, data modeling, normalization, metadata management, lineage, data quality, retention, and governance.
• Experience with observability technologies and concepts including metrics, logs, traces, alerting, telemetry, and application performance monitoring.
• Familiarity with machine learning, AI/LLM architectures, vector databases, RAG, AI agents, or intelligent automation is highly desirable.
• Ability to evaluate where deterministic automation, analytics, machine learning, and generative AI are appropriate and design platforms that can support these capabilities safely and reliably.
• Experience building systems where availability, resiliency, latency, scalability, and operational reliability are critical.
• Familiarity with video streaming technologies such as HLS, MPEG-DASH, encoding/transcoding, CDN delivery, playback telemetry, and video quality metrics is beneficial but not required.

Leadership Qualifications

• Demonstrated ability to build and lead high-performing engineering teams.
• Strong technical judgment with the ability to participate meaningfully in architecture discussions while empowering senior engineers to own