KRISHNA SINGH

- Process Opportunity Mapping: Identify high-value processes for Agentic AI using process mining and value-prioritization frameworks. - Agentic AI Solutioning: Architect multi-agent workflows and production-grade AI agents using LangChain, AutoGen, or CrewAI. - Enterprise GenAI Roadmapping: Define enterprise AI/GenAI strategy leveraging, Azure AI, Claude, Bedrock. - AI Productionization & MLOps: Scale AI from PoC to production, covering MLOps, governance, and model monitoring. - Responsible AI Advisory: Guide clients on bias mitigation, explainability, fairness, and regulatory compliance. - Value & Business Case Development: Build benchmarked, quantitative business cases for AI use cases across industries. - POC Leadership: Design and lead AI/GenAI POCs with business, engineering, and tech stakeholders. - Stakeholder Discovery & Engagement: Run discovery workshops and C-level presentations to surface AI opportunities.

- Provided strategic oversight and hands-on leadership in architecting advanced RPA frameworks, integrating data driven decision layers to transition from rule-based automation to intelligent, adaptive systems. - Mentored cross-functional teams, ensured best practices, and aligned technology initiatives with business objectives to deliver measurable operational and cost efficiencies. - Designed and deployed ML-based solutions in production using Python, Scikit-learn, and GCP data pipelines (SQL, Pandas) for enterprise process automation. - Implemented OCR and IDP workflows for document-heavy enterprise processes, driving automation using UiPath (certified Automation Architect) integrated with ML models.

- Led RPA implementation using UiPath across enterprise back-office operations; designed scalable automation frameworks with PowerShell, VBScript, and SQL integrations. - Managed stakeholder relationships and delivery of automation programs, including change management and process re-engineering.

- Delivered enterprise systems integration and automation projects, supporting back-end operations for large-scale clients.

- Engineered enterprise application integrations and system automation, contributing to infrastructure operations and service delivery.