Design, build, and operate production-grade GenAI/LLM solutions, including conversational assistants, RAG systems, document automation, AI agents, and internal copilots.
Own the end-to-end RAG stack, including chunking, embeddings, vector search, reranking, prompt design, grounding, citations, evaluation, and quality improvement.
Build document and workflow automation to extract, classify, validate, and integrate structured data into platforms such as BigQuery, DataHub, and other business systems.
Develop AI agents and tool/function-calling integrations with internal and external systems via APIs, MCP, and similar integration patterns.
Take full production ownership of AI solutions, including CI/CD, deployment, monitoring, evaluation, incident handling, cost/latency optimization, and documentation.
Implement AI governance and data protection practices, including GDPR compliance, privacy-by-design, access controls, auditability, and safeguards against hallucination, prompt injection, and data leakage.
Work closely with the AI Core Team, Data & AI Strategy Lead, engineering teams, and business stakeholders to identify use cases, evaluate whether AI is the right solution, and deliver measurable business value.
Establish reusable AI patterns, architecture, and engineering standards to support the future growth of the AI capability and team.
