Sanjeev Kumar is a seasoned IT professional with over 20 years of experience in software life cycle management, excelling in both Waterfall and Agile methodologies. He specializes in architecting and deploying multi-tier enterprise applications and cloud solutions. Sanjeev's expertise includes AWS and Microsoft Azure architectures, emphasizing performance, security, and cost efficiency. He has implemented advanced AWS and Azure security measures, designed hybrid cloud infrastructures, and managed IT operations covering networking, virtualization, disaster recovery, and governance.
Sanjeev has developed AI-driven SSO authentication systems, including PingFederate, MFA, and developed WebLogic environment creation as a Platform-as-a-Service (PaaS) solution using Chef and Ansible for automation.
Proficient in CI/CD pipelines, containerization, and shell scripting, Sanjeev has successfully led cloud migration and infrastructure optimization initiatives for major companies such as Delta Dental Insurance, Verizon Wireless, and AT&T. With a strong expertise in cloud and middleware technologies, application server management, and information security, he consistently delivers innovative IT solutions and excels in efficient project management.
As a certified AWS, Azure architect and Senior Member of IEEE and Fellow of IETE and SRC, Sanjeev is a recognized leader in cloud infrastructure, automation, and IT innovation. With a proven track record of optimizing CI/CD pipelines, driving cloud migration strategies, and advancing infrastructure efficiency for organizations such as Delta Dental Insurance, Sanjeev demonstrates a strong commitment to excellence in technology. A passionate advocate for knowledge sharing and community development, Sanjeev actively participates in mentoring initiatives and serves as a reviewer and judge for prestigious awards. Sanjeev’s technical expertise, strategic vision, and dedication to empowering the next generation of technologists make Sanjeev a driving force in the IT industry.
Sanjeev Kumar's research interests include Cloud Computing, Cybersecurity, AI, ML, Serverless Computing, DevOps, Data Security, LLMs, SSO, and Infrastructure Reliability. His work focuses on Cloud-Native Security, AI training, and CI/CD Automation.
Bringing Accuracy to Generative AI: Compute-Driven Architectures and Prompt Flow Strategies with Azure
As enterprises explore generative AI for business-critical applications, ensuring response accuracy becomes vital—especially when quantitative data and high-assurance outputs are involved. In this talk, we’ll explore how to optimize large language model (LLM) workflows using compute-augmented architecture and real-world tools such as Azure AI Studio and Prompt Flow.
Drawing from implementations in healthcare and insurance domains, this session will focus on:
• Designing pipelines that pair LLMs with compute-based validators for data accuracy
• Architecting scalable deployments with Azure Machine Learning, Prompt Flow, and Data Stores
• Structuring prompts and memory to support retrieval-augmented generation (RAG) and numerical correctness
• Addressing the limits of LLM context windows through modular design and intermediate compute
• Deploying and scaling GenAI applications with zero-downtime strategies using Azure Web App deployment slots
Attendees will gain actionable strategies to deploy GenAI models with higher reliability and accuracy while meeting enterprise scalability and compliance requirements.