Data Analytics, Python, LangChain, GenAI, data pipelines, LLMs, Hugging Face, embedding models, Pinecone, prompt engineering, OpenAI APIs, FAISS, Transformers

Cloud Computing, Software Development, Networking, Data Analytics, AWS platform services, Technology roadmaps, Large scale automation and workflow management, Security, Distributed systems design and implementation, Database design and implementation, Systems engineering, Infrastructure

snowflake , Github, Pyspark, Microservices, Azure Synapse, Terraform, Docker, Data Governance, Python, Azure DevOps, Apis, Sql, Iam, Databricks, Kubernetes, Claude, Azure OpenAI, CI CD, LangGraph, Vector Databases, AWS Data Services, RAG Architectures, LangChain, Semantic Kernel, rbac, Microsoft Fabric, OpenAI, Gemini

.NET, resiliency , Edi, Microservices, React, MySQL, Php, Authentication, AWS, Apis, SQL Server, Node.js, Devops, Rest Apis, event-driven patterns, vector databases, modular architectures, Aurora, failure handling, Authorization, AI APIs, observability tooling, observability, performance requirements, SFTP-based integrations, Messaging, Caching, ASP.NET Core

Docker, Flask, Authentication, Python, FastAPI, Kubernetes, agentic AI, AWS Bedrock, Starlette, Azure OpenAI, Azure AI Foundry, LangGraph, Google Vertex AI, cloud-native architectures, AI evaluation, REST design, CrewAI, LLMs, Claude ecosystem, API contracts, MCP vector databases, Semantic Kernel, AutoGen, Anthropic API, RAG, Microsoft Agent Framework, API architecture

Data Analytics, API-led ecosystems, presales solution shaping, insurance solution architecture, core modernization, data platforms, digital experience platforms, integration architectures, cloud-native solutions, delivery transition, AI-enabled operations

Java, Spring Boot, Kafka, DevOps practices, Microservices architecture, AWS services and infrastructure, Application security principles and practices

Python, AI services, Generative AI, modern AI ML stacks