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Fanatics

China-based licensed sports merchandise retailer

Staff Software Engineer - AI/ML Platform

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeRedwood City, CA, USA$190k - $237.5kIn-person

About the Job

Requirements

  • At least 8 years of production software development experience, including at least 2 years working on an AI/ML platform.
  • A Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • Experience designing systems across multiple services, making decisions spanning teams, and building platforms used by other engineers.
  • Strong Python and FastAPI skills, plus proficiency in at least one of Java, Go, Scala, or TypeScript.
  • Hands-on experience with Terraform, Kubernetes, Airflow, Postgres, Grafana, and Prometheus, and familiarity with the AWS data science toolkit and PyTorch.
  • Hands-on experience with large language models and generative AI on Amazon Bedrock or Vertex, including model routing, retrieval-augmented generation, tool calling, structured outputs, and context engineering.
  • Experience with agentic systems and Model Context Protocol server and client integrations; depth with runtimes such as AWS Bedrock AgentCore is valued because the technology is new.
  • Experience with retrieval data engineering, including chunking, embedding, and indexing pipelines; vector or search backends such as OpenSearch; open lakehouse table formats; and methods for measuring retrieval quality.
  • Experience with large language model evaluation and observability, including evaluation dataset design, tracing, LLM-as-judge scoring, and regression testing, using tools such as Langfuse or Arize Phoenix.
  • Experience with AI platform security and governance, including role-based access control, OAuth2/OpenID Connect, least-privilege access, cost optimization, and usage metering.
  • Clear writing and the ability to present effectively to executives.

Responsibilities

  • Own the end-to-end architecture of the AI control plane, including gateway, agent runtime, registry, retrieval, evaluation, and cost; set technical direction, sequence the roadmap, and make build-versus-buy decisions.
  • Build the enterprise large language model gateway with multi-provider routing, failover, caching, rate limiting, token optimization, and key management, with a path to self-hosted open-weight models when cost, latency, or data residency requires it.
  • Build the Agent and Model Context Protocol ecosystem on a managed runtime such as AWS Bedrock AgentCore, expose enterprise systems as governed tools over Model Context Protocol, and build a control-plane registry for discovery, ownership, versioning, and lifecycle.
  • Create a no-code path from agent prototype to governed production and surface it through a company-wide chat portal.
  • Own the unified retrieval layer and its data platform, including ingestion, chunking, embedding, and indexing pipelines and the vector and search backends; keep them reproducible, observable, and quality-gated at petabyte scale.
  • Build the evaluation and feedback loop, including offline evaluations, tracing, and regression gates in continuous integration and delivery; use production failures and user edits as new evaluation cases and attribute root causes across prompts, retrieval, tools, and models.
  • Own AI governance and cost, including role-based access control, agent identity, least-privilege access to enterprise data, audit logging, use-case-level cost attribution, and the enterprise AI tool portfolio.
  • Set engineering standards, mentor engineers, and represent the architecture and its trade-offs to senior leadership.

Desired Qualifications

  • Experience with chat user interfaces or internal developer portals.
  • Exposure to self-hosted model serving with vLLM, SGLang, or llama.cpp.
  • Familiarity with governance systems such as DataHub and semantic layers, and administering enterprise AI tools such as ChatGPT Enterprise, Claude Enterprise, or Glean.
  • Open-source contributions or published work in agentic AI or LLM operations.

About the Company

Fanatics

China-based licensed sports merchandise retailer

Fanatics China is a joint venture between Fanatics Inc. and Hillhouse Capital that localizes and scales licensed sports merchandise for China. It designs, manufactures, and markets fan gear for Chinese consumers, operating a multi-channel model that includes building and running e-commerce sites for global leagues and teams, exploring online marketplaces, and developing physical retail concepts. Its product workflow combines technology, data, and on-demand manufacturing to manage the entire supply chain, enabling fast response to demand. The company differentiates itself through a China-focused approach backed by Hillhouse’s network and investments, its end-to-end vertical commerce model, and partnerships with hundreds of sports organizations, which together help it navigate China’s complex retail landscape. The goal is to satisfy a previously underserved Chinese market for licensed sports merchandise by creating localized products and channels that connect fans with official gear.

Company size
10,001+
Company stage
Growth Equity (Venture Capital)
Total funding
$5.2B
Headquarters
Huangpu, China
Founded
1995

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