AI Engineer with machine learning expertise

- Develop AI agents that can plan and carry out business workflows involving multiple actions, including understanding inquiries, retrieving relevant context, executing tasks, confirming results, and documenting outcomes. - Convert vague business challenges into consistent agent workflows utilizing tool functions, orchestration logic, and structured outputs. - Design and implement RAG pipelines that effectively manage both structured and unstructured data, prioritizing quality retrieval and regulatory adherence. - Establish database lookup strategies using AI that comprise semantic searches, metadata filters, and corporate rules. - Connect agents to backend services through APIs and microservices, ensuring secure and reliable endpoints with auditing features. - Collaborate closely with data and platform teams to facilitate scalable and regulated access to data, considering aspects like caching, access controls, and performance logging. - Evaluate and suggest agent and RAG toolsets, executing implementations in production-grade architectures. - Set up observability measures that encompass tracing, evaluation frameworks, and drift monitoring for enhancing quality and performance. - Implement safety measures against prompt injection, output validation, and handling of personal identifiable information in line with responsible AI standards. - Define quality thresholds and fallback mechanisms to ensure agents operate safely and reliably.