Java, Python, LLMs, Azure AI, vector databases, Anthropic, OpenAI, AI applications, agent frameworks, cloud AI services, RAG architectures

Github, Machine Learning, Apis, Programming, Software Engineering, Testing, Evaluation and Traceability, Documentation, Ai, Model and Tool Integrations, Modern AI Application Patterns, AI-assisted Development Tools, MCP Observability

Apis, Microservices, response governance, enterprise knowledge architectures, AI orchestration frameworks, orchestration patterns, Generative AI, data pipelines, LLMs, retrieval optimization, integration mechanisms, tool calling, evaluation grounding, multi-agent architectures, knowledge layers, prompt engineering, vector stores, Agentic AI, hallucination mitigation, RAG, reranking, MCP context engineering

data engineering , snowflake , Java, Apache Spark, Kafka, Spring Boot, Microservices, Docker, Databricks, Kubernetes, Generative AI, Infrastructure as Code, Flink, CI CD, Iceberg, Delta Lake

lifecycle management , Devops, feedback loops, AI application engineering, Monitoring, operationalizing AI-enabled systems, agentic systems, build and release workflows, workflow automation, enterprise AI platforms, platform integration, CI CD pipelines, evaluation methods, cost-aware AI design, observability