Product Group Technology Lead - AI 4 Data Management (AI4DM)

Define and own the AI4DM product vision, roadmap, and value stream, prioritizing capabilities like agent orchestration and LLM-powered assistants.,Establish reusable AI building blocks (LLMs, retrieval, guardrails, prompt/tooling frameworks, evaluators) and an agent fabric.,Apply AI/Agents across the Data Management Delivery Lifecycle (plan → build → run → optimize) and governance activities.,Lead cross-disciplinary squads (data platform, catalog/lineage, governance, DevOps/MLOps), setting engineering standards and automation-first practices.,Integrate AI services with catalog, lineage, metadata lake, pipelines, ticketing/ITSM, workflow engines, and observability platforms.,Drive adoption via reference architectures, onboarding kits, playbooks, and reusable patterns.,Architect LLM/RAG services, tool-using agents, and rule-learning components for data discovery, classification, tagging, enrichment, lineage extraction, and data-quality assistance.,Implement guardrails, prompt standards, evaluation harnesses, and safety policies for reliable outputs and traceable decisions.,Create delivery agents for backlog curation, acceptance criteria, policy mapping, and evidence generation.,Orchestrate run-time agents for monitoring metadata freshness, control evidence assembly, exception triage, and remediation.,Codify standards and procedures into policy-as-code libraries; generate dashboards and attestations.,Automate glossary alignment, role/ownership attribution, and lifecycle checkpoints.,Use AI to recommend data-quality rules, detect drift and anomalies, and prioritize exceptions.,Establish environments, pipelines, and telemetry for model lifecycle management.,Define service SLOs and implement monitoring/alerting for agent reliability and output quality.,Partner with Data Governance, Privacy, Records & Information Management, Platform COEs, and domain teams.,Facilitate QBRs and program reviews; report outcomes, risks, and next-best actions.

10+ years across data engineering, data governance/management.,5+ years leading platform/product teams at enterprise scale.,10+ years in AI/ML engineering and Data Science.,Demonstrated delivery of AI/agent-based services for Data Management (e.g., catalog/metadata enrichment, lineage extraction, data-quality assistance, governance automation).,Strong architecture skills with LLMs, retrieval systems, agent frameworks, event/workflow orchestration, and integration with catalog/lineage/metadata platforms.,Proficiency in MLOps (model versioning, evaluation, telemetry, rollback), observability for AI services, and policy-as-code patterns.,Expertise in taxonomy/glossary design, metadata quality, and lifecycle governance practices.,Experience with multi-cloud and federated on-prem environments; privacy-preserving techniques; synthetic data generation for test harnesses; reinforcement learning from feedback to improve agent performance.