event-driven architectures (Kafka or similar, cloud-native experience (GCP, Spring Boot, Microservices, concurrency, Reactjs, Performance Tuning, Rest Apis, Python, Azure, Java ecosystem, LLM-driven capabilities, Micro Frontends, GenAI architecture patterns, Embeddings and vector databases, RAG architectures, Agent frameworks and orchestration

Java, Typescript, Javascript, Automated Testing, Cursor, Python, Azure DevOps, GitHub Copilot, Microsoft Copilot, Claude Code, Amazon Q Developer

Pytorch, Python, LangChain, Distillation, Transfer learning, Prompt engineering, Hugging Face Transformers, OpenAI function calling, PEFT adapters, Quantization, LangGraph, Agent-based orchestration, Fine-tuning transformer models, LoRA, LlamaIndex

Google Cloud Platform, Python, AI ML Generative AI, Agent Engine, Cloud Run, Agentic AI, GCP Agent Platform, Vertex AI, Google ADK, Gemini Enterprise, Vertex AI Search

Databases, Apis, Docker, Distributed Systems, Kubernetes, LangGraph, AI RAG architecture, Agentic AI LLM applications, Python backend engineering, RAG architectures

API security, AWS Identity and Access Management, Terraform, AWS CloudFormation, Python, OpenID Connect, cloud security governance, AgentCore, AWS Bedrock, Model Context Protocol, policy-based authorization frameworks, AWS Cloud Development Kit, REST API design, OAuth 2.0, infrastructure as code

Gcp, Azure, AWS, LangChain, CrewAI, vector databases, Semantic Kernel, AutoGen, LangGraph, A2A, enterprise AI workflows, RAG AI orchestration, Agentic AI, MCP, LlamaIndex

Azure, Gen AI, Ai/ml Framework