visualvm , Performance Engineering, Spring Boot, Microservices, Jprofiler, Concurrency, JUnit, Core Java, Multi-threading, JVM Tuning, GenAI, Clean Architecture, Data Flow, Semantic Kernel, LangChain4j, Automated workflows, Agentic AI, distributed architectures, Spring AI, Structured outputs, Memory Profiling

Python, LangChain, LLM Application Development, AutoGen or equivalent, Agentic Multi-step AI Workflows, REST API Integration, RAG Retrieval Augmented Generation, AI Telemetry Monitoring, Prompt Engineering

Python, LangChain, Vector Databases, Deep Learning Frameworks, LangGraph

Testing, Git, Docker, Kubernetes, LangChain, RAG systems, GenAI and Agentic AI, vector databases, embedding models, knowledge retrieval systems, prompt engineering, Crew.ai SK, Autogen, Advanced Python programming, LLM optimization techniques, async programming, RAG pipelines

Artificial Intelligence, Agentic AI, Generative AI

Automated Testing, internal automation, LLM applications, AI evaluations, prompt and context engineering, AI coding tools, Production Monitoring, API integrations, CI CD

Power Automate, Power Platform, Copilot Agent Builder, GenAI-powered assistants, LLMs, agentic AI concepts, Power Apps, Microsoft Graph, Microsoft 365 ecosystem, prompt engineering, Sharepoint, Teams, agent orchestration, Copilot Studio, conversational systems

S3, RDS, Dynamodb, Vpc, Lambda, Cloudwatch, Ec2, MLops, Docker, Terraform, Linux, Iam, ECS, Kubernetes, AWS, EKS

Uipath, Node.js, AI ML, Angular, React, REST, Gcp, Docker, Flask, FastAPI, Javascript, Python, Kubernetes, Chatbot, Agent, GRPC, Llm, WebSockets, Agentic AI, RAG, CI/CD, Streamlit, Langraph

AWS IAM, AWS Security Hub, Python, AgentCore, Multi-account AWS governance using Organizations and Control Tower, AI ML Strategy with focus on secure deployment patterns, Network security patterns for AI workloads including VPC design and private endpoints, Amazon Bedrock, AI Agents Frameworks, Amazon AWS Security