Shashank Shekhar
AI Strategy & Transformation Leader | GenAI, Agentic AI | Driving Enterprise AI Adoption, ROI & Automation at Scale | Ex Consulting | C-Level AI Programs
Bengaluru
10+ years of work experience
Jan 20242 yrs 8 mosPresent
AI Strategy & Delivery Lead | T-Systems
• Shaped the enterprise AI agenda by defining a multi-year roadmap across 16+ high-impact use cases, securing C-level sponsorship and aligning AI initiatives with business priorities and ROI objectives.
• Drove adoption of GenAI and Agentic AI across business functions by translating emerging capabilities into scalable, enterprise-ready solutions integrated with core systems such as SAP and ITSM platforms.
• Owned end-to-end accountability for AI programs, guiding cross-functional teams through ambiguity and ensuring alignment between business stakeholders, architecture, and delivery execution.
• Established governance, prioritization frameworks, and operating cadence for AI initiatives, enabling leadership visibility, structured decision-making, and consistent delivery outcomes.
• Acted as a strategic partner to business and technology leaders, influencing investment decisions, solution direction, and enterprise AI adoption strategy.
• Led AI solutioning and proposal development for key opportunities, shaping narratives, defining architecture, and contributing to pipeline growth and successful bid outcomes.
Sep 20221 yr 2 mosOct 2023
Bengaluru, Karnataka, India
• Enhanced scalability and performance of enterprise AI applications for telecom analytics (RU router data), enabling reliable anomaly detection, forecasting, and data-driven decision-making at scale.
• Improved model accuracy and system performance by identifying optimization opportunities, resolving critical issues, and enhancing overall user experience across AI-driven workflows.
• Re-architected core correlation algorithms, significantly improving scalability and analytical precision for large-scale telecom datasets.
• Designed and implemented intelligent assistant capabilities within the platform, improving user interaction, accessibility, and adoption of AI features across business users.
• Built and optimized microservices-based architecture (FastAPI, ETL pipelines, sequence mining), enabling modular, scalable, and production-ready AI components.
• Enabled continuous improvement of analytics capabilities by recommending and implementing enhancements across classification, forecasting, and insight generation modules.
Jan 20226 mosJun 2022
Bengaluru, Karnataka, India
• Developed reusable AI modules for evaluating data suitability, stability, and robustness in model validation, utilizing TensorFlow, PyTorch, pytesseract, NLTK, CV2, sklearn, pandas, and other Python libraries
• Served as a member of the Responsible-AI (RAI) review forum and council, responsible for creating and implementing a governance framework to ensure ethical development and deployment of AI technology and data usage, leveraging ICS and materiality assessment techniques
• Conducted research on creating and encrypting pip-installable packages for model validation classes, intended for future use by other teams and organizations as proprietary assets.
• Prepared monthly presentations using advanced charts generated with Plotly, Seaborn, and Matplotlib libraries, for business updates, stakeholder engagement, and MIS reporting
May 20174 yrs 9 mosJan 2022
Bangalore
• Led and delivered an end-to-end machine learning project to predict the company's attrition rate with a 0.81 recall, employing ML-based classification models and NLP techniques (text classification) using LTI employee data for model training and validation.
• Contributed to a computer vision project aimed at identifying license plates of moving vehicles on streets. The project utilized YOLO v-4 from the CV2 library, pre-trained on the COCO dataset, to capture license plates in real-time
• Engaged in continuous R&D for AI solutions such as NLP (attention-based transformers) and computer vision
• Developed action plans to mitigate decision-making risks while increasing profitability through data science applications
• Oversaw end-to-end project execution, managed risks, and ensured project quality
• Enhanced an existing AWS-based recommender system using collaborative filtering and SVD for the search feature on the Viacom web and mobile app
Jul 20152 yrsJun 2017
• Developed automated trade booking scripts using UFT (VBS), which were adopted by teams across various verticals, resulting in reduced manual effort during test cycles
• Participated in project estimation, tracking, and reporting processesc
Shashank’s AI Stack
Education
Information Technology Project Management, IT Project Management
Indian School of Business
20252025
PGP, Artificial Intelligence
Texas McCombs School of Business
20191 yr2020
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