Python, RAG systems, CI/CD pipelines, agentic AI systems, DevOps practices for AI, LLM orchestration, vector databases, AI frameworks, prompt engineering, cross-platform development

containerization , Microservices, Graphql, REST, Virtual Machines, Airflow, data pipelines, cloud-based AI services, MLflow, model orchestration, Retrieval-Augmented Generation, GRPC, LangGraph, GraphRAG, AI platform integration, Kubeflow, MLOps tools, API-driven systems, cloud-native architectures, end-to-end AI workflows, LangChain, Microsoft Azure ML, AWS SageMaker, CI CD pipelines, RAG, serving APIs, API architecture

Jenkins, Prometheus, aws, MLops, Azure, Gcp, Technical Documentation, FastAPI, Grafana, Docker, python, Kubernetes, Flask, vector databases, ai security, mlflow, langchain, aiops, gitops, Collaboration, cloud platforms, Team Leadership, github actions, airflow, opentelemetry, responsible ai, kubeflow, ai/ml application development, Mentoring

Flutter, Python, LLMs, LangGraph, Langchain, AI Implementation, OpenAI, Anthropic, Gemini

Jax, Pytorch, Python, production-grade ML systems, building training data for LLMs, domain-specific evaluations

Containers, Testing, Python, Version Control, GenAI, RAG pipelines, agentic frameworks, system reliability, fine-tuning, cloud platforms, LLMOps, vector databases, observability tools, NLP frameworks