Staff AI Software Engineer – Platform - FanDuel Careers

FanDuel

Hybrid

Quick summary

Work type: Hybrid
Location: Atlanta, GA
Salary: $170,000–$213,000 / yr
Posted: 14 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $207k

This role $192k

$158k most similar roles pay here $256k

This role pays less than 62% of similar roles. Most pay $167,100–$246,150 — the shaded band above. At the midpoint, this role pays about $192k versus about $207k for comparable roles.

Based on 240 similar postings.

Employer

About FanDuel

FanDuel is a leading online sports betting and daily fantasy sports platform operating across the United States, offering sportsbook wagering, casino games, and horse racing to millions of customers.

FanDuel currently has 2 open roles on FindRole.

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At a glance

TL;DR · Staff AI Software Engineer – Platform - FanDuel Careers

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As a Staff AI Software Engineer at FanDuel, you will lead the design and operationalization of a centralized multimodal memory architecture for enterprise knowledge management. This role involves building foundational content intelligence systems that support ingestion, indexing, embeddings, retrieval, lineage, governance, and auditability across various use cases. You will establish regulatory-compliant knowledge graphs and ontologies to create deep context about FanDuel’s products, employees, operations, customers, and systems. Additionally, you will design secure memory patterns for AI agents and ensure that all systems meet ethical standards and regulatory requirements. Key technologies include vector retrieval, graph databases, semantic search, and runtime memory evaluations. This position requires 7+ years of experience in large distributed systems, practical fluency with generative AI tools, and a strong background in regulated industries like gaming or fintech.

Skills

Python Java GraphDB RAG AgenticRAG VectorDB Ontology SemanticSearch CI/CD Docker Kubernetes AWS GCP Azure PostgreSQL Redis Git GitHub Swagger RESTful_APIs GraphQL JSON YAML Markdown Jenkins SonarQube Prometheus Grafana DynamoDB S3 Lambda CloudFormation Terraform Kafka RabbitMQ Celery Flask FastAPI SpringBoot Hibernate MyBatis SwaggerUI OAuth2 JWT OpenAPI GitLabCI JenkinsX

What you'll do

Design and operationalize a centralized multimodal memory architecture for vector retrieval, knowledge graphs, ontologies, and metadata systems.
Lead the strategy and execution for structuring and representing enterprise knowledge across AI agents and customer-facing products.
Establish regulatory-compliant knowledge graph strategies and implement deep context models using graph databases and semantic search.
Create secure design patterns for AI agent memory management to ensure efficiency, security, and compliance in regulated environments.
Ensure all knowledge systems meet ethical standards, privacy obligations, and responsible gaming principles through safeguards and monitoring.

What we're looking for

7+ years of engineering experience in large distributed systems.
Practical fluency with generative AI tools, including graph and RAG concepts.
Experience building or operating vector databases, knowledge graphs, and ontologies.
Ability to operate autonomously and influence across a matrixed organization.
Strong communication skills for both technical and non-technical stakeholders.

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