Staff Software Engineer - Enterprise Data & AI (Intelligence Platform)
Los Angeles, USA
- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign and operate production data pipelines in Databricks using bronze, silver, and gold layers
Define domain and semantic models in Unity Catalog with subject-matter experts
Own data quality with tests, monitoring, and alerting for pipelines and products
Build agents and retrieval-augmented apps grounded in governed Databricks data
Integrate enterprise systems through APIs, events, and middleware with reconciliation and auditability
From the employer’s posting
Build and operate pipelines that ingest source-system data into Databricks using a medallion architecture across bronze, silver, and gold layers
Partner with subject-matter experts to define and evolve domain, ontology, and semantic models in Unity Catalog
Own data quality for the pipelines and products you build, implementing tests, monitoring, and alerting
Build production agents and retrieval-augmented applications grounded in governed Databricks data
Integrate enterprise systems through APIs, events, and middleware while applying appropriate authentication, retries, reconciliation, and auditability.
What you’ll bring
All qualificationsCore experience
- 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 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.
Preferred experience
- 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.
Qualification wording
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 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 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.
Education & alternatives
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.
Tools in this posting
- Python
- AWS
- Databricks
- dbt
- GCP
- MLflow
- Oracle
Source — Tool mentions in context
- 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 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.
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
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.
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.
- 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.
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.
- 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.
- 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 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.
Benefits in the posting
Full benefits wording- 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.
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 20, 2026 · 38 days ago
- Recorded sightings
- 50
- Last seen by us
- Oct 28, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on www.riotgames.com. The employer’s form will show what is required.
Already applied? Track this application
Job description
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.
Source details
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- Location & working pattern
Los Angeles, USA
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