Staff AI Platform Engineer — End-to-End ML Infra

Fanatics Betting & Gaming; Redwood City (CA); On-site; USD 190,000 - 238,000; Full time

Job summary

Fanatics Commerce is seeking a Staff-level AI/ML Platform engineer to own the architecture of the AI control plane, including gateway, agent runtime, and retrieval systems. You will define standards, build the enterprise LLM gateway, and drive governance and cost oversight across complex AI tooling.

You will work hands-on with a team to ship the hardest parts, partnering with data scientists and engineers. This role demands deep systems design and a track record delivering scalable AI platforms.

Qualifications

• 8 to 12 years building production software, including 2+ years on AI/ML platform.
• Staff-level impact: system design across multiple services and teams.
• Strong python and FastAPI, plus Java/Go/Scala/TS basics and DevOps tooling.
• Experience with LLMs on Bedrock or Vertex and self-hosted options.

Responsibilities

• Own AI control plane architecture: gateway, agent runtime, registry, retrieval, evaluation, cost.
• Build enterprise LLM gateway with multi-provider routing, failover, caching, and self-hosted options.
• Develop MCP ecosystem on a managed runtime and governance tooling.
• Oversee retrieval layer and data platform, including embedding and indexing pipelines.
• Define governance, security, and cost attribution for enterprise AI tools.

Skills

Python

FastAPI

System design

Leadership

LLMs / AI

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

Terraform

Kubernetes

Airflow

PostgreSQL

Grafana

Prometheus

PyTorch

AWS Bedrock

Vertex AI

OpenSearch

vLLM

Job description

Fanatics Commerce is seeking a Staff-level AI/ML Platform engineer to own the architecture of the AI control plane, including gateway, agent runtime, and retrieval systems. You will define standards, build the enterprise LLM gateway, and drive governance and cost oversight across complex AI tooling.

You will work hands-on with a team to ship the hardest parts, partnering with data scientists and engineers. This role demands deep systems design and a track record delivering scalable AI platforms.