Docker, Distributed Systems, Python, Kubernetes, Airflow, CI/CD tools, Infrastructure automation frameworks, LLMOps, Vector databases, MLflow, Machine learning pipelines, Model training, Workflow orchestration, geospatial technologies, Model lifecycle management, DVC, MLOps practices, Large-scale data processing, Kubeflow, Cloud-native technologies

testing practices , Nosql, Java, React, Python, AWS, LangChain, pgvector, asynchronous processing, observability

alerting), Observability (logs, Retrieval-enabled architectures (RAG), Java, React, metrics, Python, LLM prompt capabilities, Event-driven and asynchronous processing patterns, tracing, Cloud-native development, Vector search embeddings, Governance expectations, CI/CD pipelines, SRE-style operational practices, Secure SDLC practices, LangChain or similar frameworks, Release automation

Retrieval-Augmented Generation (RAG) solutions, Cursor, Code, embeddings, vector search, data pipelines, vector databases, data infrastructure, AI-assisted software development tools, Document Processing, AI-powered software development tools, LLM-based applications, data quality monitoring, GitHub Copilot, Evaluation, model data pipelines, structured and unstructured data, Claude, observability, deployment workflows