Pawan kumar

1. Led 5+ ML projects implementing LLM system for synthetic data generation, OCR, invoice automation; 40% cost reduction. 2. Directed MLOps standardization across 5 units, establishing CI/CD frameworks; 40% faster time-to-market. 3. Orchestrated Terraform cloud automation; 60% faster provisioning, 25% cost reduction. 4. Deployed RAG-powered chatbots with multi-agent architecture; 25% higher user satisfaction. 5. Implemented AI compliance framework; zero bias/non-compliance incidents.

1. Led migration of applications and projects to GCP, optimizing infrastructure and enhancing scalability. 2. Forecasted and reduced compute costs for ML lifecycle. 3. Developed and implemented CI/CD and ML pipelines using MLflow, Kubeflow, and TFX. 4. Ensured scalability, security, and governance of ML infrastructure through maintenance and optimization. 5. Productionalized Generative AI solutions, including RagPowered Engines/Bots and a Prompt Engineering SaaS platform, focusing on AI and data governance.

Designed RL-based scheduling algorithm for Kubernetes clusters under EU-fundedBraine Project, improving resource utilization by 40% and reducing pod scheduling latency by 60% across distributed environments.

1. Managed installation, configuration, administration, and automation of WebSphere Application Server and Oracle WebLogic Server. 2. Set up security permissions in WebSphere environments to authenticate against LDAP servers and secure consoles using SSL. 3. Troubleshot JEE runtime environment issues by analyzing server logs, diagnosing thread-dumps, and heap-dumps using MAT, IBM heap analyzer, and Oracle Visual JVM.