Job Objectives: Lead advanced data science and agentic AI initiatives by designing scalable models, multi-agent workflows, and evaluation frameworks that deliver measurable business impact and production-ready intelligent systems on Azure.
Key Responsibilities: • Lead discovery, solution design, and technical direction for advanced ML, Gen AI, and agentic AI initiatives. • Design and optimize multi-agent workflows, role delegation, memory strategies, and reasoning patterns. • Define evaluation frameworks for models, prompts, agents, hallucination detection, cost, latency, and business outcomes. • Drive pilot-to-production readiness, governance controls, monitoring, and reusable architecture patterns on Azure. • Mentor team members and review technical quality across data science and agentic AI workstreams. • Identify and prioritize opportunities for reusable agents, orchestration templates, and automation accelerators.
Experience & Education:· Bachelor’s degree in Data Science, Computer Science,Statistics, Mathematics, Engineering, or related field.· 3–5+ years of experience in data science, machine learning, AI, or advanced analytics. · Experience leading complex enterprise ML / AI initiatives from discovery to deployment. · Hands-on experience with multi-agent systems, LLM evaluation, and Azure AI services.
Knowledge, skills and abilities:o Advanced Python, SQL, ML modeling,experimentation, and optimization.o Strong solution design across ML, LLM,agent orchestration, and evaluation frameworks.o Strong knowledge of agent-to-agent protocols,delegation, conflict resolution, and human-in-the-loop controls.o Strong understanding of hallucination detection, logging, cost / latency monitoring,and secure enterprise deployment.o Strong knowledge of Azure Open AI / Azure AI Foundry patterns and production AI governance. o MLOps / LLMOps, vector databases, orchestration frameworks, and agent graph design. o Multimodal AI design for business-driven use cases and reusable blueprint development.