Staff Application Engineer - Enterprise Data & AI (Intelligence Platform)
Riot’s Enterprise Technology organization ensures Rioters have what they need to unlock their full potential, from efficient business platforms to next-generation AI capabilities.
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.
Responsibilities:
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.
Required Qualifications:
- Bachelor’s degree in a related field, or equivalent practical experience.
- 8+ years of experience in data engineering, software or application engineering, or an adjacent enterprise technology role.
- Hands-on experience building production data pipelines, including ingestion, semantic or domain modeling, data quality, and lineage.
- Hands-on Databricks experience, including Unity Catalog, medallion architecture, and Mosaic AI or model serving.
- Hands-on experience shipping production AI solutions, such as retrieval-augmented, conversational, or agentic applications, grounded in data pipelines you built.
- Proficiency in Python and strong software engineering fundamentals, including testing, code review, CI/CD, deployment, and production support.
- Experience integrating enterprise systems through APIs, events, or middleware, including authentication, retries, reconciliation, and auditability.
- 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.
- Working knowledge of data governance, privacy, and security practices applied to production data pipelines and products.
Desired Qualifications:
- Experience with the Mosaic AI Agent Framework or Unity Catalog functions used as agent tools.
- Experience with enterprise or federated search, vector databases, or permission-aware retrieval.
- Experience with agent frameworks such as LangGraph, Pydantic AI, LangChain, or CrewAI.
- Experience with LLM or agent evaluation and observability, such as MLflow tracing.
- Experience with dimensional modeling or master data management.
- Experience integrating Workday, ServiceNow, Coupa, Concur, Oracle, OneStream, or Ironclad.
- Experience with GCP or AWS data services, dbt, containers, or serverless computing.
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.
Our Perks:
Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our benefits pages for more information.
At Riot Games, we put players first. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.
It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
- Safeguarding confidential and sensitive Company data
- Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
- Accessing Company assets, secure digital systems, and networks
- Ensuring a safe interactive environment for players and other Rioters
These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.
Skills
- Agentic AI
- AI
- Analytics
- Anthropic
- API
- Authentication
- Automation
- AWS
- CI/CD
- Cloud
- Coupa
- CrewAI
- Data Engineering
- Data Governance
- Data Pipelines
- Data Quality
- Databricks
- dbt
- Dimensional Modeling
- GCP
- LangChain
- LangGraph
- LLM
- Master Data Management
- MLflow
- n8n
- Observability
- OpenAI
- Oracle
- Python
- Serverless
- ServiceNow
- Test Automation
- Unity
- Vector Databases
- Vertex AI
As published by greenhouse · 20 questions · 1 written answer
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
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