Abhishek Rath
Hyderabad
Summary
AI Product Owner and enterprise AI leader with 12+ years of experience delivering GenAI and data-driven platforms in global banking environments. Proven in defining product vision, roadmaps, and OKRs for AI solutions spanning hyper-personalization, decision support, compliance, and enterprise knowledge platforms. Experienced in translating business goals across Retail, Operations, Risk, Compliance, and Central Functions into scalable AI products. Strong hands-on grounding in GenAI, LLMs, RAG, embeddings, and agentic architectures, partnering closely with DS, MLE, Engineering, and Business teams to take AI initiatives from ideation and MVPs to production adoption with measurable business impact.
Overview
12
12
years of professional experience
1
1
Certification
Work History
Vice President, AI & Automation
WELLS FARGO
10.2024 - Current
- Architect and lead enterprise-wide Agentic AI initiatives, managing cross-functional teams to deliver autonomous AI systems for financial operations
- Designed and deployed LangGraph-based Multi-Agent orchestration framework with Master Router architecture, reducing manual workload by 45% and improving operational efficiency across DBMS platforms.
- Implemented Model Context Protocol (MCP) pipelines with FastMCP integration, improving data processing speed by 3.2x and reducing synchronization failures by 28%
Built autonomous RAG-driven incident analysis system automating 75%+ of root cause analysis and cutting mean time to resolution (MTTR) by 40% - Developed multimodal RAG engine integrating document, image, and structured data processing, improving financial advisory accuracy by 35% and reducing analysis time to under 3 minutes
- Established Human-in-the-Loop (HITL) approval workflows and Reinforcement Learning from Human Feedback (RLHF) capabilities for compliance-critical operations
Implemented comprehensive LLMOps framework using LangSmith for evaluation, monitoring, and continuous improvement of agent performance - Led technical strategy for Agent-to-Agent (A2A) communication protocols enabling real-time streaming responses between autonomous agents
- Collaborated with senior leadership and regulatory teams to ensure AI governance, compliance, and ethical AI practices
Assistant Vice President, AI Engineering
WELLS FARGO
10.2022 - 10.2024
- Developed autonomous Agentic AI systems for predictive analytics and decision support, improving forecasting accuracy by 28% and enabling proactive risk management
- Created hybrid RAG pipeline combining semantic search with traditional databases, reducing financial report generation time by 60% while maintaining 99.2% accuracy
- Built real-time fraud detection engine using ensemble ML models and anomaly detection, reducing false positives by 30% and fraud-related financial impact by 21%
- Designed and implemented vector database architecture supporting 10M+ embeddings with sub-100ms query response times
- Established MLOps best practices including model versioning, A/B testing, and automated retraining pipelines
- Mentored team of 8 AI/ML engineers on advanced AI architectures, prompt engineering, and production deployment strategies
- Drove stakeholder alignment across product, engineering, and business teams to prioritize AI initiatives with measurable ROI
Cloud Automation Specialist
LARSEN & TOUBRO INFOTECH
03.2021 - 09.2022
- Automated Azure infrastructure provisioning using Terraform and Azure Resource Manager (ARM), reducing deployment time by 70% and infrastructure errors by 85%.
- Implemented comprehensive CI/CD pipelines achieving 99.8% deployment success rate and reducing rollback incidents by 92%.
- Designed Infrastructure as Code (IaC) frameworks enabling rapid environment replication across dev, staging, and production.
- Led Azure cloud migration projects for enterprise clients, ensuring zero-downtime transitions and 40% cost optimization.
- Established cloud governance policies and cost management strategies resulting in 30% reduction in cloud spend.
Cloud DevOps Engineer
DELOITTE
02.2019 - 03.2021
- Streamlined CI/CD pipelines using Azure DevOps and Jenkins, reducing deployment time from 2+ hours to under 10 minutes.
- Automated infrastructure provisioning and configuration management workflows, saving 300+ engineering hours annually.
- Implemented containerization strategies using Docker and Kubernetes, improving application scalability and resource utilization by 55%.
- Developed monitoring and alerting frameworks using Prometheus and Grafana, reducing incident detection time by 70%.
- Collaborated with development teams to implement DevOps best practices, improving code quality and release velocity.
Cloud DevOps Engineer
WIPRO TECHNOLOGIES
04.2014 - 01.2019
- Built end-to-end CI/CD pipelines across multiple cloud platforms, boosting deployment speeds by 3x and reducing manual intervention by 80%.
- Automated infrastructure provisioning using Ansible and Python scripting, reducing provisioning cycles by 65%.
- Designed and implemented disaster recovery and backup solutions ensuring 99.95% uptime SLA compliance.
Education
Bachelor of Technology (B.Tech) - Electronics & Telecommunication Engineering
CV Raman College of Engineering
Odisha01.2013
Technical Leadership Skills
GenAI & LLM Solutions, Retrieval-Augmented Generation (RAG), Embeddings, Agentic Architectures, Prompt Engineering, Predictive & Ensemble Models, Explainable & Responsible AI, Model Evaluation & Monitoring, Python, SQL, Large-scale Data Processing, Feature Engineering, Analytics-driven Product Insights, KPI & Metrics Design, AI Product Strategy & Roadmapping, Agile / Scrum Execution, Backlog Ownership & Prioritization, Stakeholder Alignment, GTM & Adoption Planning, Cross-functional Execution
Core Leadership Capabilities
- Owned the end-to-end AI product lifecycle, shaping vision, multi-year roadmaps, OKRs, and driving execution from MVP to scaled enterprise adoption.
- Led cross-functional and geographically distributed teams (Product, DS, MLE, Engineering, Risk, Compliance) to deliver regulated, production-grade AI platforms.
- Defined and executed GenAI product strategies for hyper-personalization, intelligent recommendations, decision support, and enterprise knowledge enablement.
- Translated complex business needs across Retail, Payments, Operations, Risk, and Compliance into clear AI problem statements and measurable product outcomes.
- Partnered with senior leadership and C-suite stakeholders to align product vision, investment priorities, and go-to-market strategies.
- Ensured sustained product success through AI governance, explainability, KPI tracking, and value realization frameworks.
Accomplishments
- Reduced operational costs by $2.5M+ annually through AI-driven automation and intelligent workflow optimization.
- Led 15+ successful AI/ML project implementations from concept to production deployment.
- Published internal technical documentation and best practices adopted across 200+ person engineering organization.
- Recognized as Subject Matter Expert (SME) for Agentic AI and Multi-Agent Systems within Wells Fargo.
- Mentored 20+ engineers in AI/ML technologies, LangGraph development, and production LLMOps practices.
Certification
- IBM RAG and Agentic AI Certification, 2025
- Supervised Machine Learning: Regression and Classification - Stanford University, 2025
- Microsoft Certified: Azure Solutions Architect Expert (AZ-303), 2022
- Microsoft Certified: DevOps Engineer Expert (AZ-400), 2022
- Microsoft Certified: Azure Administrator Associate (AZ-104), 2022
Timeline
Vice President, AI & Automation
WELLS FARGO
10.2024 - Current
Assistant Vice President, AI Engineering
WELLS FARGO
10.2022 - 10.2024
Cloud Automation Specialist
LARSEN & TOUBRO INFOTECH
03.2021 - 09.2022
Cloud DevOps Engineer
DELOITTE
02.2019 - 03.2021
Cloud DevOps Engineer
WIPRO TECHNOLOGIES
04.2014 - 01.2019
Bachelor of Technology (B.Tech) - Electronics & Telecommunication Engineering
CV Raman College of Engineering