Staff Software Engineer (Enterprise Data & AI, Intelligence Platform)

• As a Staff Data and AI Engineer on the Enterprise Data & AI team, you will build the governed data foundations that power enterprise analytics, automation, and applied AI
• Your primary focus will be data architecture and data engineering, where you will be responsible for designing and operating production data pipelines in Databricks, integrating & curating data through a medallion architecture, and defining semantic and domain models in Unity Catalog with subject-matter experts
• You will also build agents and retrieval-augmented applications directly on this governed data using Databricks capabilities such as Unity Catalog functions, Mosaic AI, and model serving
• You will own your systems from architecture through production operations, applying strong engineering, data quality, security, evaluation, and observability practices throughout
• The ideal candidate is a hands-on data and software engineer who can turn ambiguous enterprise needs into reliable data products and focused AI-enabled solutions
• The role will report to the Senior Manager, Enterprise Data and AI
• Data Pipelines and Semantic Layer (Primary):
• Build and operate pipelines that ingest source-system data into Databricks using a medallion architecture across bronze, silver, and gold layers, with lineage, provenance, access controls, and logging
• Partner with subject-matter experts to define and evolve domain, ontology, and semantic models in Unity Catalog, then curate reliable data products into those models
• Own data quality for the pipelines and products you build, implementing tests, monitoring, and alerting so issues surface before they reach downstream consumers
• Integrate enterprise systems through APIs, events, and middleware while applying appropriate authentication, retries, reconciliation, and auditability
• Agents on the Databricks Data Layer (Secondary):
• Build production agents and retrieval-augmented applications grounded in governed Databricks data, using Unity Catalog functions as tools and Mosaic AI or model-serving capabilities
• Add authorization, approvals, and auditability for consequential actions performed through agents or AI-enabled orchestrations
• Create evaluation sets and observability for the agents you ship, including groundedness, latency, cost, and production feedback, and use the results to improve them
• Engineering Fundamentals:
• Apply solid engineering practices, including automated testing, code review, CI/CD, documentation, on-call support, and concise design notes
• Own architecture decisions for your systems and communicate material tradeoffs clearly to technical and business partners

Benefits

• Healthcare: Medical, dental, and vision plans that cover you as well as your spouse/domestic partner and children.
• Family Care: Life insurance, parental leave, plus short and long-term disability.
• Open Paid Time Off: In addition to holidays, a 2-week end of year break, and a 1-week mid-year break, Rioters are trusted to take the time they need throughout the year.
• Retirement: Riot matches retirement contributions so you can continue to play games long after you retire.
• Play Fund: Riot’s annual play fund allows Rioters to broaden their knowledge of the games that matter to players and the community.
• Donation Matching: Riot matches donations of time and money to nonprofits to double down on support.

• For this role, you’ll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes your fellow Rioters, who are the customers of your work. Being a dedicated fan of games is not necessary for this position
• Bachelor’s degree in a related field, or equivalent practical experience
• Experience integrating enterprise systems through APIs, events, or middleware, including authentication, retries, reconciliation, and auditability
• 8+ years of experience in data engineering, software or application engineering, or an adjacent enterprise technology role
• Proficiency in Python and strong software engineering fundamentals, including testing, code review, CI/CD, deployment, and production support
• Experience with an LLM or cloud AI platform such as Vertex AI, Anthropic, or OpenAI and an automation platform such as Workato, n8n, Camunda, or similar
• Hands-on Databricks experience, including Unity Catalog, medallion architecture, and Mosaic AI or model serving
• Hands-on experience building production data pipelines, including ingestion, semantic or domain modeling, data quality, and lineage
• Working knowledge of data governance, privacy, and security practices applied to production data pipelines and products
• Hands-on experience shipping production AI solutions, such as retrieval-augmented, conversational, or agentic applications, grounded in data pipelines you built
• Experience with dimensional modeling or master data management
• Experience with GCP or AWS data services, dbt, containers, or serverless computing
• Experience with enterprise or federated search, vector databases, or permission-aware retrieval
• Experience with the Mosaic AI Agent Framework or Unity Catalog functions used as agent tools
• Experience with LLM or agent evaluation and observability, such as MLflow tracing
• Experience with agent frameworks such as LangGraph, Pydantic AI, LangChain, or CrewAI
• Experience integrating Workday, ServiceNow, Coupa, Concur, Oracle, OneStream, or Ironclad