Role Description As an AI Microservices Developer, you will be responsible for creating APIs that leverage Large Language Models (LLMs) and Generative AI models to build products and perform business process automation tasks. You will be expected to manage your own projects, develop them in Python, and work with the DevOps team to deploy these projects as micro-services in a cloud environment. You will support game services, products, games, and internal functions across the organization. This role sits on Side’s Artificial Intelligence team and reports to the Head of Artificial Intelligence. The team serves as the hub for AI and machine learning across the entire organization and all our brands. We collaborate on cross-functional projects that range from internal tools to user-facing product features. You will partner with stakeholders throughout the organization to align on requirements, set expectations, and deliver API solutions. Key Responsibilities - Develop and Architect Python-based API Microservices that make calls to LLMs and other generative models to support business needs. - Work on Python-based API Microservices that provide AI-enabled and LLM powered solutions for business needs. - Keep up with the latest LLM technologies including OpenAI, Llama and Gemini. - Understand and become the company’s expert in LLM and Generative AI API methods and Open Weights model deployment. - Work as a product manager to understand the business needs for business process automation tasks. - Turn business needs into API requirements for microservices. - Work with the DevOps team to ensure deployment of the Python-based APIs are live and kept functional. - Assist in the integration of your API microservices with other software and tools throughout the organization. - Refine and optimize AI systems throughout the project lifecycle to ensure performance and functionality across platforms. - Write and debug core AI code, ensuring maintainable and scalable solutions. - Develop tools and utilities to support AI development and testing. - Proactively identify and address challenges related to AI development, devising creative and effective solutions. - Maintain regular communication with cross-disciplinary teams to ensure cohesive development. Qualifications - Bachelor's degree in Computer Science, Engineering, or a related field. - 2+ years of experience developing Python-based REST APIs. - Experience with OpenAI LLM APIs. - Understanding of micro-services architecture and ability to design scalable architectures from the ground up. - Knowledge of databases and programming APIs that use databases (NoSQL or SQL). - Experience coding with Python frameworks such as Flask, Django, FastAPI or similar. - Basic Web Application Architecture Knowledge. - Able to interact with business leaders across the organization to understand and manage requirements. Desired Qualification - Experience with LLM technology stacks and a variety of service and model options including OpenAI, Anthropic, and Open Weights models. - Experience with AI Image Generation pipelines. Requirements Note: Specific requirements may vary depending on project needs. Benefits Available to fulltime employees.

• Developing, and maintain the backend services and frontend interfaces for our custom, internal security tools • Leveraging AI-driven development tools to accelerate development, testing, and debugging workflows • Collaborating with the team through rigorous code reviews and active architectural planning • Creating and maintain comprehensive technical documentation to support system design and knowledge sharing • Participating actively in agile ceremonies to drive project velocity and transparent team communication

• Pipeline Re-architecture: Migrate and re-architect legacy Perl batch jobs and crontab pipelines into modern Python-based services. • Workflow Orchestration: Design and implement orchestration using Prefect or Airflow, including alerting, observability dashboards, and safe job re-run capabilities. • Modern Observability: Instrument services with structured logging and metrics (CloudWatch, or Grafana) to eliminate the need for direct production server access. • Data Layer Ownership: Manage the data layer for file ingestion: landing raw scheme files to S3, parsing/transforming them, and persisting to PostgreSQL or RDS for reconciliation. • Financial Domain Logic: Process and reconcile payment scheme files (clearing, settlement, chargebacks) from card schemes and acquirers. • Engineering Standards: Contribute to architecture decisions, write technical documentation, and establish best practices across the team.

• System Implementation: Support the re-architecture of legacy Perl batch jobs into modern, maintainable Python services. • Operational Reliability: Assist in implementing workflow orchestration (Prefect/Airflow) to ensure safe job re-runs and system stability. • Observability: Help instrument our services with logging and alerting (Grafana/CloudWatch) so we can monitor systems without direct production access. • Data Transformation: Work on data ingestion pipelines, moving raw data to S3 and transforming it into relational database records.