Backend Platform Engineer - AI Operations Platform

Make your mark at Comcast -- a Fortune 30 global media and technology company. From the connectivity and platforms we provide, to the content and experiences we create, we reach hundreds of millions of customers, viewers, and guests worldwide. Become part of our award-winning technology team that turns big ideas into cutting-edge products, platforms, and solutions that our customers love. We create space to innovate, and we recognize, reward, and invest in your ideas, while ensuring you can proudly bring your authentic self to the workplace.

Join us. You’ll do the best work of your career right here at Comcast. (In most cases, Comcast prefers to have employees on-site collaborating unless the team has been designated as virtual due to the nature of their work. If a position is listed with both office locations and virtual offerings, Comcast may be willing to consider candidates who live greater than 100 miles from the office for the remote option.)

This Software Engineer (Engineer
3) focuses on building scalable backend microservices, robust API layers, and multi-tenant platform infrastructure for our AI Ops platform. Rather than academic model training, this role drives pragmatic engineering execution—integrating backend tools, database systems, and AI/ML wrappers into reliable, production-grade services that serve both modern and legacy systems across multiple teams

Join our core platform engineering team, where you will design, build, and scale production-grade systems that support critical business capabilities. In this role, you will focus on pragmatic engineering execution, developing high-throughput microservices, API layers, and backend infrastructure. You will help drive the integration of our AI Ops platform by bringing together tools, services, and AI-enabled capabilities into a unified, multi-tenant environment.

Working across both modern and legacy technologies, you will play a key role in connecting platform innovation with existing systems while supporting a diverse set of internal and external stakeholders

This position is ineligible for visa sponsorship. To be considered for this role, you must be legally authorized to work in the United States and not require sponsorship for employment now or in the future.

• Architect and scale a multi-tenant AI Ops platform integrating backend services, runtime engines, and developer tools.
• Evaluate technology choices, provide technical recommendations, and set engineering standards for consuming platform services.
• Design end-to-end technical solutions and collaborate directly with external and cross-functional teams on integrations.

• Design, build, and maintain high-concurrency GraphQL and REST APIs to handle core platform communication and data exchanges.
• Develop resilient, event-driven backend microservices and clean abstraction layers.
• Build wrappers, gateway routers, and middleware around AI/ML models to deliver practical operational tools at scale.

• Design, optimize, and maintain relational and No
  
  SQL database schemas for high-throughput production workloads.
• Implement system telemetry, logging, and performance metrics across cluster environments to ensure uptime and observability.
• Containerize and deploy services using modern CI/CD pipelines and orchestration tools.

• 5+ years of hands-on experience designing, scaling, and operating distributed backend systems and microservices.
• Proven track record of designing and implementing GraphQL and REST APIs for complex system communication.
• Practical, hands-on experience deploying and scaling real-world AI/ML use cases, serving tools, and API wrappers focusing on operational execution rather than theoretical modeling.
• Direct experience designing, optimizing, and querying relational (e.g., PostgreSQL) and/or No
  
  SQL databases at scale.
• Advanced proficiency in Python (and/or Go, Java, or C++).
• Proven ability to architect complex systems, evaluate technical tradeoffs, and work with external engineering teams.

• Experience with Docker, Kubernetes, and managing…