Staff Engineer Software

At Fanatics Betting & Gaming (FBG), a core division of Fanatics' mission to establish the ultimate end-to-end digital sports platform, we're crafting a world where every aspect of a sports fan's passion is catered to. On the engineering side, we're pioneering the use of AI as a code collaborator. We need engineers who have gone beyond experimentation: engineers passionate about min/maxing their workflows who actively experiment with Claude Code, Cursor, Git Hub Copilot, or similar tools to ship production code faster while maintaining exceptional quality standards.

If you have strong opinions about AI-augmented development workflows backed by real experience, we want to talk with you. As a Staff Engineer, you'll be a technical leader shaping the architecture of our entire betting platform. You'll define technical strategy across multiple teams while maintaining hands‑on technical excellence. This role requires someone who can balance deep technical expertise with strategic thinking and cross‑functional influence.

You'll lead by example, establishing best practices for AI‑assisted development while building systems that handle millions of events daily.

• 10+ years building and deploying scalable, high‑performance production applications
• 5+ years in technical leadership roles
• Experience with systems handling 100M+ daily transactions
• Track record of successful multi‑team technical initiatives
• Kotlin and/or Java: 5+ years building production microservices
• Spring Boot:
  Deep understanding of reactive programming and non‑blocking I/O
• Postgre
  
  SQL:
  Complex query optimization, indexing strategies, and migration management
• Kafka:
  Event streaming patterns, partition strategies, and consumer group management at scale
• Redis/Redis Pub/Sub:
  Building real‑time features supporting hundreds of thousands of concurrent users

• Proven ability to influence technical decisions across an organization
• Experience defining technical standards adopted by 50+ engineers
• History of mentoring senior engineers to staff‑level roles
• Can point to specific architectural decisions that unlocked business value
• Track record of introducing tools or processes that measurably improved team velocity

• Has introduced AI development practices at team or organization level
• Can articulate ROI and present business cases for AI tool adoption
• Experience building internal tooling or frameworks enhancing AI effectiveness
• Demonstrated experience using AI tools (Claude Code, Cursor, Copilot, etc.) to ship production code
• Can articulate specific examples of workflow improvements (e.g., "reduced boilerplate generation time by 40%")
• Has developed personal strategies for validating AI‑generated code and identifying common pitfalls
• Can compare at least 2‑3 AI tools with concrete pros/cons from actual usage
• Strong grasp of software design principles (SOLID, DRY) and testing methodologies (TDD, BDD)
• Experience with observability and monitoring in distributed systems
• Self‑directed problem solver who thrives in ambiguous situations
• Team‑first mentality with willingness to jump in wherever needed
• Actively experiments with and optimizes personal development workflow
• Strong written and verbal communication skills

• 7+ years building and deploying scalable, high‑performance production applications
• Kotlin and/or Java: 3+ years building production microservices
• Spring Boot:
  Deep understanding of reactive programming and non‑blocking I/O
• Postgre
  
  SQL:
  Complex query optimization, indexing strategies, and migration management
• Kafka:
  Event streaming patterns, partition strategies, and consumer group management at scale
• Redis/Redis Pub/Sub:
  Building real‑time features supporting hundreds of thousands of concurrent users
• Demonstrated experience using AI tools (Claude Code, Cursor, Copilot, etc.) to ship production code
• Can articulate specific examples of workflow improvements (e.g., "reduced boilerplate generation time by 40%")
• Has developed personal strategies for validating AI‑generated code and identifying common pitfalls
• Can compare at least 2‑3 AI tools with concrete pros/cons from actual usage
• Strong grasp of…