Neo4j, AI ML, MLops, MongoDB, production-grade reliability, AWS Bedrock, re-ranking, vector databases, responsible AI controls, LangGraph, AWS Neptune, embedding, chunking, output evaluation, document pipelines, DORA metrics, engineering standards, similarity thresholds, LangChain, RAG architecture, LLMOps, managed inference infrastructure, hallucination detection, SageMaker, LLM orchestration frameworks, prompt tracing, data-driven model evaluation, AI observability, knowledge graph architectures

Ml, Apis, cloud security, Vulnerability Management, Cybersecurity, Devops, Software Architecture, Application Security, Gcp, Cloud Infrastructure, Azure, Python, AWS, Generative AI, LLMs, Ai, secure software development, RAG AI agents, CI CD practices

Pytorch, Tensorflow, Azure ML, Deep Learning, MLops, Machine Learning, AWS SageMaker, Google AI, computer science fundamentals, LLM fine-tuning, training methodologies, Scikit-learn