AI System Developer III

AI System Developer III

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. The position emphasizes deep expertise across retrieval-augmented generation (RAG), multi-agent orchestration, and model fine-tuning, while accelerating enterprise delivery through AI-assisted development and mentoring of less experienced team members.

Essential duties and 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.
• Write and review unit, integration, and acceptance tests for AI components and APIs; contribute to evaluation framework improvements; participate in release planning, deployment verification, and post-deployment monitoring; troubleshoot complex production issues, perform root-cause analysis, and implement durable fixes or mitigations; provide on-call support as required.
• Mentor Level I and Level II developers through code review and technical guidance; create and maintain technical documentation, runbooks, and API documentation; support business stakeholders with training and adoption playbooks; and contribute reusable patterns, templates, and components to the Center of Excellence knowledge base.
• 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.

Education:

• 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.

Experience/Specific Knowledge:

• 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.
• Minimum of four (4) years of development experience in modern software engineering languages and environments; 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…