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Fanatics · 1 month ago

Software Engineer II - Java, Kotlin, Kafka

95 Morton St, New York, NY, 10014, US

Full-time

Onsite

Mid Level

$130K/yr - $180K/yr

4+ years exp

Fanatics is a leading company in the sports industry, focused on creating a premier digital sports platform. The Software Engineer II role involves developing and optimizing real-time systems for their sports betting platform, with a strong emphasis on AI-assisted development practices.

eSportsManufacturingRetailSporting GoodsSports

No H1B

Responsibilities

Design, build, and optimize real-time betting systems handling 10K+ events per second

Ensure 99.999% uptime for customer-facing services through robust error handling and failover strategies

Optimize database queries, caching strategies, and event streaming pipelines for sub-100ms response times

Feature ownership: spec writing → implementation → deployment → monitoring → iteration based on metrics

Self-motivated with an ability to have an idea, build it, and support it!

Leverage AI tools to accelerate development velocity while maintaining code quality standards; ability to identify and prevent common AI-generated code pitfalls (over-abstraction, missing edge cases, security vulnerabilities)

Qualification

JavaKotlinKafkaSpring BootPostgreSQLRedisAI toolsSoftware design principlesTechnical documentationProblem solving

Required

4+ years building and deploying scalable, high-performance production applications

Java and/or Kotlin: 3+ years building production microservices

Spring Boot: Understanding of reactive programming and non-blocking I/O

PostgreSQL: 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

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)

Track record of introducing tools or processes that measurably improved team velocity

Experience with observability and monitoring in distributed systems

Can write clear technical documentation and present architecture decisions to non-technical stakeholders

Actively experiments with and optimizes personal development workflow

Self-directed problem solver who thrives in ambiguous situations with a willingness to jump in wherever needed

Preferred

Experience in sports betting industry or genuine interest in sports

Previous experience in high-growth startup environments

Contributions to open-source projects or technical community

Experience with real-money transaction systems and regulatory compliance

Background in building developer tools or improving engineering productivity

Note on AI Workflow: We're serious about AI-augmented development. During interviews, be prepared to: Demo your current AI-assisted workflow. Discuss specific examples of how you've used AI to solve complex problems. Share your strategies for ensuring AI-generated code meets production standards