AI Transformation Leader | IBM | Enterprise GenAI & Agentic AI at Scale | AI Strategy, Delivery & Business Value Realization
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Assessing your cultural and operational fit
AI leader with 20+ years of experience, including 14+ years specialising in AI/ML and 3+ years in GenAI. Built and scaled a 240-engineer GenAI Client Engineering practice at IBM from the ground up. Drives revenue and business development across EMEA (Germany, Austria, Switzerland), architecting enterprise AI solutions for Fortune 500 clients across financial services, energy & utilities, retail, healthcare, and oil & gas. Co-authored IBM Redbook on AI Governance; holds 5 patents in AI and data systems. Combines deep technical expertise in LLMs, RAG, and ML with executive-level stakeholder engagement and P&L ownership.
Harvard Extension School
CSCI E-90, Cloud Computing and the Internet of Things
January 1, 2016 – January 1, 2017
Aegis School of Business, Data Science & Telecommunication
IBM certified Executive Post Graduate Program/MS , in Data Science, Business Analytics and Big Data
January 1, 2016 – January 1, 2017
National Institute of Technology Hamirpur-Alumni
Bachelor of Technology (B.Tech.), Electrical, Electronics and Communications Engineering
N/A – Present
IBM
AI Lead
June 1, 2023 – Present
IBM
Senior Manager (Cognitive and Data Science)
October 1, 2018 – May 1, 2023
Accenture
Technology Architecture & Science Manager - Artificial Intelligence/Data Science
March 1, 2017 – October 1, 2018
Bengaluru, Karnataka, India
Wipro Technologies
Lead Consultant - Data Science
September 1, 2014 – March 1, 2017
Manthan Systems
Lead Consultant - Big Data Analytics
May 1, 2014 – September 1, 2014
HP
System Engineer
May 1, 2006 – April 1, 2014
Bengaluru, Karnataka, India
Robert Bosch GmbH
Senior Software Engineer
June 1, 2004 – May 1, 2006
Bengaluru, Karnataka, India
ITI Limited
Engineer (R&D)
January 1, 2000 – January 1, 2004
Greater Bengaluru Area
Sentiment Analysis using Twitter data
November 1, 2013 – Present
Sentiment Analysis was done during Delhi Assembly elections, December 2013. The project included algorithm implementation in R using twitter feeds.
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Microsoft Certified: Azure Fundamentals
Microsoft
June 24, 2026 – Present
Project Management Professional (PMP)
Project Management Institute
June 24, 2026 – Present
Data Scientist Certification Course
UNext For Enterprise
June 24, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong cultural fit for an innovative, fast-paced, and client-centric environment. Their career progression through major technology companies (IBM, Accenture, Wipro, HP, Bosch) indicates adaptability and a drive for continuous learning and leadership. The diversity of projects across various domains (energy, utilities, financial services, retail, automotive) and technologies (GenAI, traditional ML, Big Data) showcases a broad skill set and willingness to tackle diverse challenges. The emphasis on mentoring, establishing talent frameworks, and fostering an innovation culture aligns well with organizations valuing growth and development. The target role of 'Data Analyst' seems significantly under-leveled given the candidate's extensive senior leadership and architectural experience in AI/Data Science; they are clearly qualified for much more senior roles like 'Lead Data Scientist', 'AI Architect', or 'Head of Data Science'.
Soft Skills & Operational Fit
The candidate's extensive leadership roles (AI Lead, Senior Manager, Technology Architecture & Science Manager) demonstrate strong operational fit for senior positions, emphasizing team growth, talent frameworks, innovation culture, and end-to-end solution delivery. The descriptions highlight strategic thinking, collaboration with diverse teams (business, data, technology), and establishing governance frameworks, indicating strong soft skills in leadership, communication, and stakeholder management. The experience in client-facing roles (Fortune 500 clients, RFP solutioning) further supports a strong operational fit.