• Design, develop, and maintain scalable, high-performance REST APIs using Django REST Framework. • Collaborate closely with front-end developers, other back-end developers, product owners, scrum master, solution architect, QA, and other team members to define and implement requirements. • Optimize and refactor existing codebases for better performance, reliability, and security. • Ensure the codebase follows best practices, including testing, code reviews, and documentation. • Integrate third-party services and APIs as required, ensuring data consistency and reliability. • Maintain and improve back-end data structures, managing databases and optimizing queries.

• Design and build backend-heavy platform features for our platform • Productionalise AI-enabled capabilities (e.g. anomaly detection, recommendations, agent-based workflows) • Implement AI thoughtfully across the entire SDLC - prototyping, testing, iteration, and deployment • Collaborate closely with Product to turn vision into shipped features • Identify blockers early, communicate clearly, and iterate fast • Help shape engineering standards and patterns as the product matures • Design systems that support model evaluation, prompt/version management, and deterministic fallbacks to ensure AI-driven features are observable, testable, and production-safe • Build AI features with explicit evaluation criteria, feedback loops, and guardrails (accuracy, latency, cost, and explainability) so models improve predictably over time • Success in the first 6–12 months looks like: 2+ production-ready features shipped. Tangible progress towards operating as a smart intelligence platform. Clear, repeatable engineering patterns for AI-enabled development. Utilize lightweight but rigorous AI engineering practices (evaluation harnesses, rollout strategies, and rollback mechanisms) that allow the platform to scale AI features safely and repeatedly.

• Designing and building Python-based backend services • Developing APIs using FastAPI • Designing and maintaining event-driven architectures • Managing large-scale data ingestion and ETL workflows • Working with MongoDB • Deploying and maintaining AWS serverless services • Supporting secure B2B API integrations • Improving reliability, performance, and system scalability

• As a microservices developer, build software systems that have well-defined interfaces • Write modular and reusable code and deliver high-quality results for enterprise projects • Develop, test, and deploy high-quality software into production • Own the delivery of small to mid-sized features and components from design through implementation • Work through project and task roadblocks, collaborating with teammates and escalating when needed • Contribute to and help drive technical and design discussions within the team • Make implementation trade-off decisions and contribute to solution design • Debug and troubleshoot issues across environments, including production • Participate in the on-call rotation to support production systems • Take ownership of problems, propose solutions, and ensure resolution or proper handoff • Participate in code reviews, providing and incorporating feedback to improve code quality • Contribute to team planning, estimation, and prioritization discussions • Support software quality, customer experience, and maintainability by contributing to automated testing • Work closely with product teams and internal stakeholders to inform technology decisions • Mentor and support engineers earlier in their careers • Must be open to occasional travel to Fanatics Betting & Gaming offices and other locations