Lead AI/ML Engineer - R01572495

Lead AI/ML Engineer Job requirements Experience Range: With at least 4 to 6 years of experience designing, building, and operationalizing enterprise-scale AI platforms, including hands-on expertise in agentic AI, LLMs, and Azure-based solutions. Key Responsibilities: - Design, build, and deploy AI agents and multi-agent systems using Azure AI services, Azure OpenAI, and modern agentic frameworks such as Semantic Kernel, LangChain, LangGraph, and AutoGen. - Develop and operationalize agentic workflows for business functions, integrating AI solutions with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and enterprise APIs. - Implement enterprise RAG solutions utilizing Azure AI Search, vector search, hybrid search, and semantic ranking to enhance knowledge retrieval and business decision-making. - Build production-ready AI applications leveraging LLMs, RAG pipelines, tool/function calling, memory systems, and workflow orchestration for scalable, secure, and reliable enterprise deployment. - Establish observability, guardrails, responsible AI controls, evaluation, security, and monitoring for AI applications in production environments. - Optimize agent and LLM applications for latency, accuracy, reliability, scalability, security, and cost, applying advanced techniques and metrics. - Collaborate with cross-functional teams to identify AI opportunities, rapidly prototype solutions, and iterate based on user feedback. - Contribute to internal best practices around agent architecture, prompting, RAG, model selection, evaluation, and AI engineering standards. Required Skills: - Hands-on experience with Azure AI services, Azure OpenAI, and Azure AI Foundry - Expertise in agentic frameworks (Semantic Kernel, LangChain, LangGraph, AutoGen) - LLM application development and prompt engineering - Enterprise RAG architectures and vector search technologies - Integration with Microsoft 365, Teams, SharePoint, Dynamics 365, Power Platform, and APIs - Python programming for AI/ML solutions - ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras) - AI workflow orchestration tools (KubeFlow, BentoML) - Model evaluation and observability tools (Evidently AI, Great Expectations) - AI security and governance on Azure Preferred Skills: - Experience with Azure Functions, Azure Container Apps, Azure Kubernetes Service (AKS), and Azure Storage - Proficiency in R and R Studio for statistical computing - Knowledge of SAS or SPSS for advanced statistical modeling - Familiarity with microservices, event-driven architectures, and enterprise integrations - Expertise in developing reusable agent frameworks, prompt libraries, and deployment patterns Desired Qualifications: - Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline - Certification in Machine Learning or Data Science from a recognized institution (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning Specialty, Microsoft Certified: Azure AI Engineer Associate) - Certification in statistical analysis tools or platforms (e.g., SAS Certified Statistical Business Analyst)