Embed responsible AI practices into AI solution design, development, and operations. Assess risks involving fairness, privacy, safety, transparency, security, and regulatory impact; define governance controls and approval gates; review LLM, RAG, and agentic systems; establish documentation, monitoring, human oversight, and audit evidence; and coordinate remediation with engineering, legal, compliance, security, and product teams.

Lead end-to-end architecture for agentic AI solutions, including multi-agent workflows, tool calling, memory, retrieval, human-in-the-loop controls, and cloud deployment. Define security, resilience, scalability, latency, cost, observability, and governance standards. Select models, cloud services, vector search technologies, and frameworks while evaluating build-versus-buy decisions. Establish AIDLC stages, architecture decision records, evaluation criteria, release gates, and AI safety controls for banking-critical systems.

Designs, experiments with, deploys, monitors, and evaluates machine learning models. Requires full-stack development involving Python, React, AWS, APIs, and SQL, along with statistical and probabilistic foundations. The role supports AI/ML initiatives in a consulting environment serving financial services and energy clients.