Software Engineer II

Fanatics

28d•Remote

About The Position

As Software Engineer II at Fanatics Betting & Gaming (FBG) with a focus on AI and Machine Learning, you will play a crucial role in our team's ambitious initiative designed to leverage AI and data-driven systems to transform customer operations into a market differentiator. You'll architect and enhance sophisticated data infrastructure and pipelines that fuel AI-driven insights, real-time conversational analytics, predictive troubleshooting, and contribute to the development of intuitive UI screens and tools that empower customer success teams. You will be collaborating closely with data scientists, ML engineers, and cross-functional teams, and your work will significantly impact operational efficiency, customer engagement, and innovation within FBG.

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.

Nice To Haves

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.

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.