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

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

Apis, Python, experiment tracking, AI development stack, Agentic AI frameworks, data pipelines, knowledge graphs, multimodal systems, deployment designs, retrieval logic, autonomous AI systems, agent workflows, document intelligence, responsible AI, production AI monitoring, Vertex AI, cloud-native architectures, secure AI architecture, automated tests, GCP services

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