data engineering , ML Libraries (scikit-learn), Version Control (Git), PyTorch), Containerization (Docker), Deep Learning Frameworks (TensorFlow, Data Processing (pandas, Orchestration (Kubernetes), NumPy), Java, Spring Boot, Python, Machine Learning, Distributed Systems, Artificial Intelligence, Restful Services, Agentic AI, Microservices Architecture, API Design Principles, Event-driven Architectures

Cloud Architecture, Devops, Git, Pandas, MLops, Gcp, Docker, FastAPI, Azure, Python, vector search, reranking models, unstructured data embedding, LLM applications, Langfuse, RAG, document parsing

Kafka, Spring Boot, Grafana, JIRA, Datadog, Nosql, Tensorflow, Pytorch, Docker, Swagger, Python, AWS, Java, Google Cloud, Sql, New Relic, Rabbitmq, Django, Jenkins, FastAPI, Postman, Azure, GitHub Actions, GitLab CI, RESTful API design

Microsoft Power Bi, Data Modeling, Power Query, Sql, Star-schema design, Advanced DAX, Semantic model development, Power BI Fabric capacity optimization, Dataflow creation management

Web Application Development, Data Science, Database Design, Agentic AI frameworks, AI techniques, Agile delivery methodologies, containerisation and orchestration, cloud computing platforms, automated build test and deployment pipelines

Cloud deployment, Scalability, Gcp, System Design, Python, AWS, modern backend frameworks, LLMs, DevOps practices, Reliability, agent-based systems, multi-agent workflows, model optimization

Advanced Analytics, Data Management, Performance Testing, Data Architecture, automation, AI machine learning, Agile delivery, agentic AI applications

Docker, FastAPI, Kubernetes, Python, CI CD pipelines, Kubeflow, MLflow

Python, model SDKs, AWS Strands, AWS Bedrock, GLM, Azure AI Foundry, Gen AI, LangGraph, LLMOps practices, DeepSeek, Qwen, Google Vertex AI, vector DBs