Summary of Bio:
- AI Strategy & Enterprise Architecture for Data-Driven Businesses
- Turning Complex Business Problems into Executable AI Strategies
- Trusted Advisor in AI, Data, and Enterprise Architecture
- Building AI-Enabled, Data-Driven Digital Enterprises
- From Data to Decisions: AI Strategy, Architecture, and Execution
- AI, GenAI & Data Architecture for Real-World Business Impact
- Where Enterprise Architecture Meets Practical AI
Shirish is a passionate problem solver and pragmatic enterprise strategist and architect who has spent more than 20 years helping organizations turn complex business challenges into clear, executable AI and technology strategies. He is known for his ability to decompose complicated problems into simpler, solvable pieces and then craft solutions that are both elegant and practical.
An early pioneer of cloud-native software, Shirish has served as a Principal / Senior Enterprise Architect and hands-on engineer, developing technology visions and strategies that improve enterprise efficiency and business productivity through agility and business composability. He designs architectures and operating models that are tightly grounded in business drivers and total cost of ownership (TCO)—covering runtime efficiency, deployment, operating models, auditing, compliance, and governance.
Shirish’s work increasingly centers on AI, machine learning, GenAI/LLMs, and data & analytics. He helps enterprises monetize and operationalize their data—living his conviction that “data is the new oil.” As a trusted advisor to senior leadership, he shapes AI vision and strategy, builds roadmaps, and guides teams in turning that vision into reality. He is equally comfortable working with experienced data scientists and “citizen data scientists,” providing platforms, patterns, and simple, accessible ways to leverage advanced AI responsibly and at scale.
He has deep experience in the Financial Services domain and is an expert in Investment Management. Shirish has designed and developed multiple systems for large investment management firms, impacting front, middle, and back office functions, as well as trading and trade processing. His interests include bringing machine learning, cloud computing, and big data analytics into trading, risk, and operations workflows to drive higher ROI and better decision-making.
Shirish is also passionate about high-quality engineering. He has a special interest in writing and refactoring code so that systems are adaptable, extensible, scalable, and efficient, and has extensive experience re-engineering existing systems to meet these standards.
Beyond delivery, Shirish is committed to teaching and mentoring. He actively mentors developers, architects, and data professionals and has led training and skilling initiatives—helping both technical and non-technical audiences understand core concepts in AI, data science, and modern software engineering.
An entrepreneur at heart, Shirish is active in the Boston startup community. He served as Chair of the MIT Enterprise Forum Cambridge – Software Entrepreneur Group for five years and was a founding member of the group for 11 years. He has been involved in a variety of startups focused on data, AI, and software innovation.
Shirish is an alumnus of MIT Short Programs. He holds a BA in Mathematics, Economics, and Computer Sciencefrom Wabash College, and a Master of Science in Applied Economics and a Master of Science in Computing from Marquette University. His computing thesis was on “Peer-to-Peer Distributed Computing” (an early exploration of what we now call cloud computing), and his economics thesis focused on valuing currency options portfolios using VAR models and interval analysis.
Contact Shirish :
Shirish (dot) Ranjit at shirishranjit.com