Staff DevOps Engineer

About the role

As the Staff DevOps Engineer, you will be responsible for leading our DevOps and platform engineering initiatives, fostering a culture of automation, continuous integration, observability, reliability, and delivery. Your efforts will support consumer data-driven advertising and marketing products, standardized consumer identity solutions, machine learning platforms, and emerging AI-powered applications across NBCUniversal and its brands.

You will partner with engineering, data, security, and AI teams to design and operate scalable cloud platforms that enable application development, analytics, machine learning, and AI workloads.

Your expertise in AWS services, Infrastructure as Code, container orchestration, observability, platform automation, and cloud architecture will be critical in building secure, resilient, and cost-effective environments that accelerate innovation while maintaining enterprise governance and operational excellence.

You will operate in an individual contributor capacity, but as a Staff Engineer, you will lead and mentor more junior DevOps Engineers, fostering a culture of innovation, continuous improvement, operational excellence, and platform-first thinking.

Responsibilities

• Develop and lead the implementation of DevOps, Platform Engineering, and Site Reliability Engineering (SRE) practices to improve the efficiency, scalability, reliability, and security of cloud-based applications and services.
• Design, build, and maintain robust CI/CD pipelines that automate software delivery, infrastructure deployment, platform provisioning, and operational workflows.
• Architect, deploy, and manage scalable AWS cloud infrastructure supporting applications, data, machine learning, and AI workloads.
• Implement and manage containerization and orchestration platforms (Docker, Kubernetes, EKS) to ensure consistent, secure, and resilient environments across development, testing, and production.
• Establish and maintain Infrastructure as Code (Terraform, CloudFormation) and Git Ops practices to improve platform consistency, governance, and operational efficiency.
• Build and support ML Ops and AI platform capabilities, including model deployment automation, inference platform operations, AI workflow orchestration, secure API integration, and lifecycle management for AI-enabled services.
• Enable secure integration of AI platforms, LLM-based applications, vector databases, agent frameworks, and machine learning services while ensuring compliance with enterprise security and governance standards.
• Develop observability solutions using logging, monitoring, tracing, and operational analytics platforms to proactively detect performance issues, infrastructure anomalies, security risks, and AI workload health concerns.
• Design scalable cloud architectures that support high availability, disaster recovery, cost optimization, and AI workload scalability.
• Partner with Security, Data, and Architecture teams to implement cloud security controls, identity and access management, secrets management, and compliance requirements across traditional and AI-enabled platforms.
• Drive automation of infrastructure operations, environment provisioning, platform governance, and operational processes to reduce manual effort and improve developer productivity.
• Maintain comprehensive documentation, operational runbooks, architecture standards, and platform governance processes

Qualifications & Requirements

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related field, or equivalent professional experience.
• 6+ years of experience in DevOps, Platform Engineering, Cloud Engineering, or Site Reliability Engineering, including experience operating at a senior or technical leadership level.
• Strong hands-on experience with Terraform and Infrastructure as Code, including building, deploying, and maintaining cloud infrastructure at scale.
• Deep experience with AWS and core cloud services such as EC2, EKS, ECS, S3, RDS, DynamoDB, Lambda, IAM, CloudWatch, and VPC networking.
• Strong experience with containerization and container orchestration technologies, including Kubernetes, EKS/ECS, and Docker.
• Experience designing, building, and maintaining CI/CD pipelines using technologies such as Jenkins, GitHub Actions, GitLab CI/CD, AWS CodePipeline, or similar tools.
• Experience supporting high-traffic, high-throughput consumer-facing applications or platforms, with demonstrated knowledge of scalability, performance, availability, and production reliability.
• Experience implementing observability and monitoring using tools such as Datadog, Splunk, ELK, Prometheus, Grafana, OpenTelemetry, or CloudWatch.
• Strong understanding of cloud security practices, including IAM, secrets management, networking, and secure infrastructure design.
• Experience designing scalable platform architectures that balance reliability, performance, governance, and cost optimization.
• Ability to provide technical leadership and mentorship to engineers while remaining a hands-on individual contributor.
• Excellent communication and collaboration skills with the ability to work across engineering, data, security, and architecture teams.

Desired / Preferred Qualifications

• Experience supporting large-scale, high-volume platforms processing 5,000+ transactions per second (TPS).
• Experience supporting high-visibility live or tentpole events where traffic can increase significantly and platform availability is business-critical.
• Experience working in multi-cloud environments, particularly Microsoft Azure in addition to AWS.
• Experience with data pipeline orchestration and supporting data-intensive platforms.
• Experience deploying or operating Model Context Protocol (MCP) servers or similar technologies.
• Familiarity with agentic AI architectures, agent workflows, AI skills, and AI-enabled application infrastructure.
• Experience supporting LLM-based applications, AI/ML workloads, model-serving infrastructure, inference services, or related AI platform capabilities.
• Familiarity with AI platform security, governance, operational monitoring, and secure API integrations.

Pay and benefits

This position is eligible for company sponsored benefits, including medical, dental and vision insurance, 401(k), paid leave, tuition reimbursement, and a variety of other discounts and perks. Learn more about the benefits offered by NBCUniversal by visiting the Benefits page of the Careers website. Salary range: $130,000 - $160,000 (bonus eligible)