Fanatics is building a leading global digital sports platform, and they are seeking a Software Engineer II to focus on AI and Machine Learning initiatives. The role involves architecting and enhancing data infrastructure to support AI-driven insights and collaborating with cross-functional teams to improve operational efficiency and customer engagement.
Responsibilities:
- Architect, build, and manage robust data pipelines and infrastructure that support large-scale AI and machine learning initiatives
- Develop and optimize integrations between core AI services, including AWS Bedrock, LLMs, and internal platforms (Salesforce, Tableau, Slack) for enhanced operational performance
- Collaborate with applied scientists and ML engineers to refine model deployments, feature engineering, and ensure seamless operationalization of predictive and conversational AI solutions
- Implement advanced data processing and real-time analytics workflows for conversational intelligence, sentiment analysis, and predictive troubleshooting
- Ensure high-quality data management, emphasizing security, compliance, data governance, and maintainability within AI-driven environments
- Drive tooling and infrastructure solutions that facilitate efficient testing, debugging, monitoring, and continuous improvement of AI applications
- Establish comprehensive observability frameworks (logs, metrics, alerts) to maintain system reliability, performance, and operational insights
- Participate actively in technical discussions, code reviews, and strategic planning to align AI infrastructure development with business goals
- Proto-type and develop intuitive, user-friendly UI screens and dashboards that enable customer success teams to leverage AI-driven insights effectively
Requirements:
- 3 -7 years of professional experience focused on data engineering, specifically supporting AI, ML, or NLP-driven systems
- Deep expertise in cloud technologies (AWS highly preferred), including hands-on experience with AWS Bedrock, Redshift, MongoDB, and S3
- Proficiency in Java, Sprintboot, and experience with orchestration tools (Airflow, Prefect) for managing complex AI-driven workflows
- Demonstrated experience integrating and operationalizing Large Language Models (LLMs) and machine learning systems within production environments
- Strong understanding of microservices, RESTful API development, and real-time data streaming (Kafka, Kinesis)
- Robust experience with observability tools and CI/CD pipelines, ensuring the reliability and continuous deployment of AI services
- Exceptional problem-solving abilities, comfortable navigating ambiguity, and adept at collaborating across technical and business-focused teams
- Extensive experience specifically with AWS Bedrock or equivalent managed AI services
- Proven track record in building real-time AI analytics systems, predictive troubleshooting tools, and advanced NLP-driven applications
- Experience working with Salesforce or other related products or a firm understanding of customer success workflows
- Background in customer-centric operations, including AI-driven customer service solutions, chatbots, and contact center technologies
- Familiarity with sentiment analysis, conversational analytics, and predictive modeling in dynamic, consumer-facing environments
- Passionate about AI trends, data engineering best practices, and their practical application in high-impact industries such as gaming, sports betting, or customer engagement platforms
- Experience building front-end applications using modern frameworks (React, Angular, Vue) and familiarity with UI/UX design principles