Manikumar Vajji

About Manikumar Vajji

Understand the Business problem, challenge of existing technologies and area of application for AI technologies.Identify and choose right AI or Cognitive computing technologies for solving problems and formulate AI receipe for development.Develop required machine learning models or prototype applications applying formulated AI receipe and verify the problem fit.Involve in development of AI platform projects.

Experience

1. Gen Ai Product & Transformation Leader

   Equitable

   Jan 2020 — Present · Charlotte, NC, US

   PRODUCT STRATEGY & MANAGEMENT Own end-to-end product lifecycle for enterprise Gen AI platform serving knowledge workers across multiple divisionsDefine product vision, strategy, and roadmap for LLM-powered solutions leveraging GPT-4, Claude, and Azure OpenAIDeveloped prompt engineering frameworks and reusable RAG template library, significantly reducing development timeDrive adoption strategy including change management, training programs, achieving strong user adoption ratesDIGITAL TRANSFORMATION - INTELLIGENT UNDERWRITINGLed major digital underwriting transformation initiative, architecting Gen AI-powered straight-through processing using Azure OpenAIDesigned intelligent document understanding agents using GPT-3.5/GPT-4 and RAG for automated extraction and risk assessmentImplemented prompt engineering strategies for early NIGO detection, substantially reducing NIGO ratesDramatically reduced application processing time, significantly increased underwriting capacityDeveloped explainable AI (XAI) capabilities for regulatory compliance and underwriter trust-buildingTEAM LEADERSHIP Built and mentor high-performing cross-functional team of AI/ML engineers, data scientists, and product managersPivoted team skills from traditional ML to Gen AI/LLM expertise in 2022 through structured training programsEstablished AI/ML competency framework and career development pathsChampion knowledge sharing through monthly workshops on prompt engineering, RAG architectures, and agent frameworksTRADITIONAL ML & INFRASTRUCTURE Established AI/ML infrastructure and traditional machine learning pipelines supporting predictive modelingBuilt supervised learning models for underwriting risk assessment using Scikit-learn, XGBoost, and Spark MLlibDeveloped MLOps practices includes model versioning, A/B testing, and performance monitoring

Education

• Andhra University

  Bachelor's degree, Electrical, Electronics and Communications Engineering

  2002 — 2006

• Stevens Institute of Technology

  Master's degree, Applied Artifitial Intelligence (AAI)

Skills

• Etl
• Sdlc
• Databases
• Tableau
• Business Intelligence
• Datastage
• Oracle
• Requirements Analysis
• Netezza
• Unix
• Business Analysis
• Birt
• Team Leadership
• Control-M
• Cognos
• Data Analysis
• Requirements Gathering
• Data Warehousing
• Sql