AI System Developer III

About the role

The AI System Developer III serves as a senior individual contributor responsible for the design, development, integration, and support of complex AI-enabled solutions, enterprise integrations, and advanced microservices. This role operates with a high degree of independence and contributes to solution design decisions, reusable architectural patterns, and the technical maturity of the AI Center of Excellence.

Responsibilities

• Design, implement, and optimize retrieval-augmented generation (RAG) solutions including vector store design, knowledge index management, chunking strategies, embedding model selection, and retrieval quality evaluation.
• Contribute to the design and implementation of multi-agent systems, agentic call flows, and LLM fine-tuning and adaptation for domain-specific use cases; includes agent-to-agent communication patterns, tool use, memory management, training data preparation, and model evaluation.
• Design, implement, and maintain complex AI system components including model serving APIs, advanced inference pipelines, and production-grade microservices.
• Implement and optimize integrations between LLMs, AI services, and enterprise applications including internal portals, chatbots, and workflow automation platforms.
• Apply and contribute to AI governance guardrails and security controls including data minimization, PII detection and redaction, prompt injection mitigation, content moderation, adversarial input handling, and model output validation; collaborate with Legal, Compliance, and Security to implement controls required for regulatory frameworks and internal policy adherence.
• Translate complex business requirements into technical specifications, flow diagrams, solution designs, and implementation plans with minimal supervision.
• Work with Data & Analytics to define, access, and prepare AI-ready datasets; ensure data quality, lineage, and appropriate transformations for model training and inference workloads.
• Contribute to and improve CI/CD pipelines, containerization strategies (Docker/Kubernetes), model versioning, model registry practices, and MLflow workflows to support reliable and repeatable AI delivery.
• Create and maintain comprehensive technical documentation, runbooks, user guides, and API documentation for engineering and business audiences.
• Perform all duties with tact, courtesy, and professionalism; work effectively across multi-disciplinary teams; maintain regular, dependable attendance and a high regard for personal safety, company assets, and the general public; and perform other duties as assigned.

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.
• A Master's degree in Computer Science, Machine Learning, or a related field is preferred.
• A minimum of seven (7) years of direct work experience in IT or a related discipline may be considered as a substitute for a degree.
• Minimum of four (4) to five (5) years of overall IT experience.
• Minimum of four (4) years of recent experience focusing on system development, support, implementation, and upgrades with demonstrated AI/ML components.
• Strong proficiency in Python and common ML/AI libraries and frameworks required.
• Demonstrated hands-on experience deploying and optimizing LLMs (open-source or API-based) in production environments.
• Demonstrated experience designing and implementing RAG solutions including vector store selection, embedding pipelines, and retrieval quality tuning.
• Demonstrated experience designing and implementing agentic or multi-agent systems using orchestration libraries and frameworks.
• Experience with model fine-tuning, instruction-tuning, or domain adaptation including training data preparation and evaluation.
• Experience in the full product development life cycle including design contribution, development, testing, deployment, and post-production support.
• Established SQL skills in MS SQL and/or Oracle databases and working knowledge of data engineering patterns.
• Experience with reporting tools and the ability to develop and maintain operational and audit reports.
• Experience in an application development environment using web frameworks, microservices, Microsoft .NET or equivalent technology.
• Experience implementing AI security controls including PII handling, prompt injection defense, content moderation, and output validation.
• Experience effectively communicating business and technical issues to both technical and non-technical audiences.
• Advanced proficiency in MS Office applications including but not limited to Excel, Word, Access, PowerPoint, and Outlook.