- Chief Architect owning disruptive technology strategies and initiatives- Data , AI, Infra Architecture Strategy, Innovation & Planning- driving architecture effectiveness for traditional AI and Generative AICurrent Role:  AI Strategy and Planning – define short term and long-term AI strategy for my customers and have a concrete roadmap to implement them. Led AI strategies for Manufacturing customers driving success in 1 year, increasing ROI by 15%. AI Risk Management – apply thought process to identify risks associated with AI for the business and control, mitigate and monitor them. Led Model Risk Management team to control, monitor, mitigate risks associated with 50+ AI/ML models. Risks were related to Credit Risk, Customer Service Risk and Process related risks. Implement AI@Scale and performance – bring frameworks to implement AI right from Ideation to Productionization. Led MLOps and LLMOps team to industrialize ML solutions on until production. Automated monitoring of Data Drift and Model Drift and added efficiency by 20% reducing time and effort to re-train and re-deploy models.  Bring Innovation and Disruptors – recently did poc on GitIngest and LLMOps. Implemented Architecture solution for Ryder Cup Golf Tournament on AWS platform bringing Sports Analytics capability.  AI Product Integration – integrate different business channels with AI Chatbot and add value to business channels.  Xops adoption – implement XOps for my customers where X== dev, data, AI, ML, LLM, RAG, Agent Cost Optimization and Control – bring necessary automations to have continuous control and monitor Cloud platform cost  AI Governance – bring enterprise level Governance framework for Data and AI Cloud Security: Cloud Security, Data Privacy, Data Security, Information Security, DDOS implementations.

- Platform Engineering for Generative AI POCs/ MVPs and end-to-end projects- Productionization multiple ML / Deep Learning service endpoints on Mobile devices - build end-to-end machine learning platform (starting data ingestion -> data curation -> dataset training -> ML model register -> ML model deploy -> ML Model monitoring ).- work closely with teams to convert POCs to full fledge development project and ultimately productionalize AI models to production environment.- Machine Learning Engineering on Production- Own Sustainability Initiatives to reduce Carbon Emission across AI Consmption Platforms (AICP) on Cloud

- Automated various Machine Learning Lifecycle steps like Data Prep, Model Training, Model Registration, Model Inference, Model Scoring, Model Deployment, Model Performance Monitoring and Hyperdrive on Azure, AWS & GCP platforms - SME for optimizing performance and availability of NLP based model service endpoints - Created solution for multi-model deploy under one single service endpoint.- Created platform for MLOps pipeline at On-Premise Ecosystem using Gitlab -> Artifactory -> Kubernetes.- Architected Image Processing services using Azure Machine Learning (AML), Ensemble and Azure Kubernetes Service (AKS). Defined Strategy for AML Compute Management using ACI (Azure Container Instance) and AKS- SME for Plotly Dash applications- Define Hybrid Cloud Strategy using AI Bursting techniques- Handling Generative Adversarial Networks (GAN) models like Enlighten-GAN etc

Created integration solution for different private cloud applications and Azure Services and performed code promotion till production using devops pipelines. Also, automated devops pipelines for various Infra requirements using Azure Powershell.

Created DevOps and DataOps pipelines on Azure DevOps

ALM Portfolio Manager, ALM Architect (using tools stack like Bitbucket, Jenkins, Concourse, Artifactory, Dynatrace , Splunk, Ansible, Fisheye/Crucible, Jira, MetaCenter, ELK, Confluence ) . Specialties in:- Java based end-to-end design and development in Windows and Linux environments.- CICD implementation using Atlassian/Compuware/SonaType/IBM products for different Java based apps, Machine Learning Regression models, Python Apps. - Integration Architecture and related implemention for enabling Private Cloud in Fidelity Data Centers - Designing backup strategies using Active-Passive model for Atlassian Products like Bitbucket, Confluence, Fisheye/Crucible. - Prior experience in creating Application Architecture and Design for Investment Management with JPMC- Delivering Agile Scrum and Kanban trainings and implementation. Past experience as Scrum Master and Technical Lead for Java /J2EE applications (on-premise datacenter) and Python based applications on AWS.

Past - Associate Architect in Accenture

Worked as a technical consultant for JPMC (8 months as on deputation in JPMC, London, UK) and Visa Europe (1.5+ yr as on deputation in Reading, UK) while being with TCS.

Worked as a technical consultant for Lehman Brothers and JPMC while being with TCS, Bangalore.

Developed applications for Defence Accounts Department,Govt of India,Bangalore.