Explore state-of-the-art data and AI techniques, including agentic patterns, evaluation methods, AI-native developer tools, and modern data architectures, and turn them into capabilities that make our Data Engineering, Analytics, and Data Science teams measurably faster: AI-accelerated pipeline development, intelligent alerting, and natural-language access to data.8+ years across data engineering, analytics engineering, software engineering, or ML engineering, with the last 3+ years building and shipping Applied AI and agentic LLM systems in production. Production discipline for AI systems: evaluation harnesses, guardrails, and telemetry that change decisions (offline evals, golden sets, LLM-as-judge, behavioral regression, drift monitoring), and optimization for cost, latency, throughput, and inference quality (model selection, serving decisions, token-spend control, caching, batching, streaming, distillation, quantization, speculative decoding).