AI System Developer I

Responsibilities

• Support the implementation and maintenance of AI system components including model serving APIs, inference pipelines, and microservices under the direction of senior developers.
• Assist in implementing integrations between LLMs, AI services, and enterprise applications including internal portals, chatbots, and workflow automation platforms.
• Learn and apply retrieval-augmented generation (RAG) concepts including vector stores and knowledge indexes under the guidance of senior team members.
• Aid in translating business requirements into technical specifications, flow diagrams, and implementation plans with supervision.
• Leverage AI-assisted development tools to support Rapid Application Development (RAD) including generating code scaffolding, templates, unit-test stubs, and documentation under established guidelines and patterns.
• Support data preparation activities in collaboration with Data & Analytics; assist in ensuring data quality, lineage, and appropriate transformations for AI-ready datasets.
• Assist in packaging AI components using containerization (Docker) and support deployment automation activities (Kubernetes, serverless patterns) under direction.
• Support CI/CD pipeline activities for model and service delivery; learn and apply model versioning and model registry practices (MLflow, model registry) under supervision.
• Apply company AI governance guardrails under direction: data minimization, PII handling, prompt filtering, content moderation, and privacy and security best practices; support collaboration with Legal, Compliance, and Security as needed.
• Write unit and integration tests for AI components and APIs under supervision; participate in release planning, deployment verification, and post-deployment monitoring; assist in troubleshooting production issues and documenting findings; maintain technical documentation, runbooks, and user guides as assigned; provide on-call support as required.
• Keep current with LLM, generative AI, and MLOps best practices; learn and apply reusable patterns, templates, and components from the Center of Excellence knowledge base.
• Work effectively across multi-disciplinary teams and present technical details to non-technical stakeholders.
• Collaborate with a variety of people with tact, courtesy, and professionalism.
• Maintain regular, dependable attendance and a high level of performance.
• Maintain a high regard for personal safety, the safety of company assets and employees, and the general public.

Qualifications

• Bachelor's degree from an accredited institution in Computer Science, Machine Learning, Data Science, Software Engineering, Information Systems, Business Management, or a related discipline.
• Minimum of three (3) years of direct work experience in IT or a related discipline may be considered as a substitute for a degree.
• Foundational experience or academic exposure to system development, AI/ML concepts, or software engineering practices.
• Foundational development experience in modern software engineering languages and environments; exposure to Python and common ML/AI libraries and frameworks preferred.
• Exposure to or coursework in the full product development life cycle.
• Basic SQL skills and foundational understanding of data concepts and structures.
• Exposure to reporting tools and the ability to assist in developing and maintaining operational reports.
• Fundamental experience or coursework in application development using web frameworks, microservices, or equivalent technology.
• Ability to communicate technical and business issues clearly to both technical and non-technical audiences with supervision.
• Ability to manage assigned tasks and priorities with regular supervision and guidance.
• Proficiency in MS Office applications including but not limited to Excel, Word, PowerPoint, and Outlook.