Senior Media Platform Engineer

Fox•Tempe, AZ

10d

About The Position

Our Senior Media Platform Engineer role will build and operate the workflow orchestration and integration layer that powers FOX’s internal software-defined media services and AI-enabled workflows. This position focuses on developing the “glue” between platforms—workflow engines, microservices, APIs, data stores, and observability—so FOX can reliably deploy, scale, and support AI-assisted media capabilities across production and distribution environments. This role works closely with multiple engineering teams and operational stakeholders to translate user needs into repeatable, governed workflows (POC → pilot → production) using modern software engineering practices and cloud-native delivery patterns. You will help FOX standardize how workflows are defined, validated, released, and monitored—especially for high-value AI use cases such as transcription, dubbing, highlights, video/audio analysis, and generative media services.

Requirements

5+ years professional software engineering experience building and operating production services (APIs, microservices, distributed systems)
Strong experience with cloud-native development practices: containers, service orchestration concepts, and CI/CD delivery
Solid programming ability in one or more common backend languages (e.g., Python, Go, Java, TypeScript) and comfort building RESTful APIs and integrations
Experience integrating with data systems (SQL/NoSQL), message/event systems, and modern authentication/authorization patterns
Experience evaluating and integrating practical AI/ML capabilities into production systems, including automation, intelligent monitoring, workflow optimization, or developer tooling
Strong troubleshooting mindset: ability to debug production issues and implement durable fixes
Strong communication skills and comfort working cross-functionally with technical and non-technical stakeholders

Nice To Haves

Experience with workflow orchestration tools or event-driven architectures
Familiarity with observability tooling and SRE-style operational practices (SLIs/SLOs, alerting, postmortems)
Understanding of modern AI technologies such as LLM APIs, vector databases, and inference services, with the ability to apply them pragmatically in scalable, reliable environments
Experience integrating AI/ML inference services, MLOps patterns, or contributing to model evaluation/fine-tuning workflows
Familiarity with Kubernetes/OpenShift operations and infrastructure-as-code concepts
Exposure to live media/broadcast concepts (helpful, but not required—we can teach)
Bachelor’s Degree or equivalent practical experience in Engineering, IT, Computer Science or related technical field

Responsibilities

Design and implement workflow orchestration for media and AI pipelines (job definitions, routing rules, scheduling constraints, approvals, retries, and error handling)
Build and maintain platform services that standardize how workflows are executed and governed across environments (dev/test/prod)
Develop reusable workflow templates, SDKs, and integration patterns that accelerate delivery and reduce one-off implementations
Implement policy and guardrails for workload isolation (e.g., real-time vs batch vs experimental) in partnership with platform/SRE teams
Partner with AI/ML stakeholders to evaluate model options (build vs buy vs fine-tune), including selection criteria such as quality, latency, cost, and operational complexity
Support model implementation into production workflows, including packaging, versioning, deployment patterns, rollback strategies, and reproducibility
Contribute to model lifecycle practices such as dataset/labeling requirements, evaluation/benchmarking metrics, A/B testing approaches, and periodic model refresh processes
Help operationalize model governance: traceability of model versions, model performance monitoring in production, and release notes tied to workflow versions
Implement workflow-level validation and acceptance checks (input validation, output verification, automated quality gates) to ensure reliable, repeatable outcomes
Define “production-ready” criteria for workflows (telemetry, error handling, documentation, runbooks, support handoffs) and enforce them through automation
Partner with operations and reliability teams to ensure workflows can be supported in a 24/7 environment, with clear escalation paths and on-call expectations where appropriate
Build production-grade services with strong engineering discipline: code reviews, automated testing, secure coding practices, and documentation
Implement and improve CI/CD pipelines for workflow services (build, test, deploy, promote, rollback) in partnership with platform teams
Ensure services are observable and supportable (structured logs, metrics, tracing, dashboards, and operational runbooks)
Perform root cause analysis and automate repetitive operational tasks to reduce toil and improve reliability
Work across engineering teams and stakeholders (Broadcast, Video, Monitoring & Control, Networking, Media Infrastructure) to define requirements, evaluate alternatives, and deliver the best solution for FOX workflows
Translate user and operator requirements into clear user stories and acceptance criteria (“As a user, I need… ”)
Support internal clients (MCR/operations, production engineering, distribution teams) and, when applicable, improve FOX’s ability to support external partners through better reliability, visibility, automation, and repeatable delivery patterns