Staff Platform Engineer

Fox•Tempe, AZ

About The Position

Build and mature the shared AI platform that MediaCloud teams use to deliver AI-enabled products and workflows, with a strong early focus on agentic workflow capabilities. This senior individual contributor role turns early AI patterns and pilot implementations into reusable, observable, governed platform capabilities that other engineering teams adopt.

Requirements

Hands-on experience using AI agentic workflows and AI code-generation tools (for example, Claude Code, Cursor, or equivalent) as the primary way to produce code.
Treats code review as a first-class discipline — reviews AI-generated and human-written code with equal rigor, spots subtle correctness, security, and maintainability issues, and holds a high bar on what ships.
Strong software engineering background, ideally in platform engineering, developer tooling, or shared internal systems.
Production experience on AWS, with working knowledge of AWS AI and data services (Bedrock, SageMaker, Transcribe, Rekognition, S3, Lambda, ECS/EKS).
Experience designing and operating APIs, workflow orchestration, and service integrations at production scale.
Working knowledge of AI-enabled applications, LLM-based systems, agentic workflows, or applied automation.
Track record of designing systems for change — swappable components, clear interfaces, upgrade paths — so the platform absorbs new AI tooling as it emerges.
Track record leading complex technical work that spans multiple teams.
Strong judgment on reliability, observability, maintainability, and cost.
Clear written communication.
Comfortable defining technical direction in writing for other senior engineers.

Nice To Haves

Experience in media, broadcast, or content-heavy environments.
Experience shipping vector search and retrieval systems (Chroma, OpenSearch, pgvector, etc.).
Experience building or operating agentic frameworks (tool-use, planning, multi-step orchestration).
Experience integrating multiple model providers behind a common interface.

Responsibilities

Build shared agentic workflow components, orchestration primitives, and integration services used across MediaCloud teams.
Design the platform for modularity so individual agents, models, frameworks, and tools can be swapped as AI tooling evolves.
Implement platform standards for model access, prompt and workflow versioning, evaluation, observability, and reliability.
Build on AWS AI and data services (Bedrock, SageMaker, Transcribe, Rekognition, S3, Lambda, ECS/EKS) as the preferred runtime surface.
Partner with the Staff AI Solutions Engineer to decide what belongs in the shared platform and what stays team-owned.
Support pilot and early-adopter teams by shipping reusable platform capabilities they can build on directly.
Contribute to evaluation, telemetry, and support patterns so platform usage is measurable and supportable.
Translate AI strategy into concrete technical implementation, with strong opinions on APIs, interfaces, and integration contracts.
Use AI agentic workflows and code-generation tools as the primary way to produce code, and set the review bar for code that ships.
Document platform capabilities so any engineer on the team can operate and extend them.