Product Group Technology Lead AI for Data Management

Product Group Technology Lead AI for Data Management

At TD, we are committed to providing fair and equitable compensation and growth opportunities. As a Product Group Technology Lead AI for Data Management, you will be instrumental in designing, building, and scaling AI methods and agent-based services. Your work will automate and augment every aspect of Data Management, from discovery and classification to governance workflows and delivery lifecycle orchestration across cloud and on-prem environments.

Role Summary

The Product Group Technology Lead AI for Data Management owns the vision, implementation, and product leadership for AI and AI Agents. This role transforms metadata, policies, and operational signals into actionable automation and continuous intelligence, driving innovation in data management practices.

Accountabilities

• Product & Platform Ownership: Define and own the AI for Data Management product vision, roadmap, and value stream, prioritizing capabilities such as agent orchestration, LLM-powered assistants, and intelligent workflow automation.
• AI Methods & Agent Fabric: Establish reusable AI building blocks (LLMs, retrieval, guardrails, prompt/tooling frameworks) and an agent fabric for various Data Management capabilities.
• Lifecycle Coverage: Apply AI/Agents across the Data Management Delivery Lifecycle (plan → build → run → optimize) and governance activities, ensuring repeatable and audit-ready outcomes.
• Engineering Leadership: Lead cross-disciplinary squads, setting engineering standards, SLAs/SLOs, and automation-first practices for reliable, scalable AI services.
• Enterprise Integration: Integrate AI services with catalog, lineage, metadata lake, pipelines, ticketing/ITSM, workflow engines, and observability platforms for closed-loop automation.
• Adoption & Change Enablement: Drive adoption through reference architectures, onboarding kits, playbooks, and reusable patterns, enabling safe and consistent consumption of AI capabilities.

Key Responsibilities

• Design & Build AI Capabilities: Architect LLM/RAG services, tool-using agents, and rule-learning components for data discovery, classification, enrichment, lineage extraction, and data-quality assistance. Implement guardrails, prompt standards, and safety policies.
• Agentized Delivery Lifecycle: Create delivery agents for backlog curation, acceptance criteria, policy mapping, and evidence generation. Orchestrate run-time agents for monitoring metadata freshness, control evidence assembly, and exception triage.
• Governance Automation: Codify standards and procedures into policy-as-code libraries for agent interpretation and application, generating audit-ready dashboards and attestations.
• Data Quality & Intelligence: Use AI to recommend data-quality rules, detect drift and anomalies, prioritize exceptions, and enable auto-healing patterns. Provide insight packs on posture and improvement opportunities.
• MLOps & Reliability: Establish environments, pipelines, and telemetry for model lifecycle management. Define service SLOs and implement monitoring/alerting for agent reliability and output quality.
• Stakeholder Leadership: Partner with Data Governance, Privacy, and platform teams to align policies and technical design decisions. Facilitate QBRs and report outcomes, risks, and next-best actions.

Qualifications

• 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.
• Excellent stakeholder leadership and communication across governance, platform, and delivery teams.
• Experience with multi-cloud and federated on-prem environments; privacy-preserving techniques; synthetic data generation; reinforcement learning from feedback.

Who We Are

TD is a leading global financial institution, recognized as the fifth largest bank in North America by branches. We are dedicated to making every interaction remarkably human and refreshingly simple for over 27 million households and businesses worldwide. With more than 95,000 colleagues, TD fosters deeper relationships, ensures disciplined execution, and builds simpler, faster banking experiences, constantly reimagining what banking can be.

Our Total Rewards Package

Our comprehensive Total Rewards package reflects our investment in colleagues' financial, physical, and mental well-being. It includes a base salary, variable compensation, health benefits, savings and retirement programs, paid time off, banking benefits, career development opportunities, and reward and recognition programs.

Additional Information

We are delighted you're considering a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we're committed to providing the support our colleagues need to thrive both at work and at home.

Colleague Development

TD supports your career path and skill development with regular performance conversations, access to an online learning platform, and various mentoring programs, helping you unlock future opportunities. We foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential.

Training & Onboarding

We provide comprehensive training and onboarding sessions to ensure you have everything needed to succeed in your new role.

Interview Process

Candidates of interest will be contacted for an interview. We strive to communicate outcomes to all applicants promptly via email or phone.

Accommodation

Your accessibility is important to us. Please inform us if you require accommodations (e.g., accessible meeting rooms, captioning for virtual interviews) to ensure your full participation throughout the interview process.

Key skills/competency

• AI and Machine Learning
• Data Management
• Data Governance
• LLM/RAG Architectures
• MLOps
• Product Leadership
• Stakeholder Management
• Enterprise Integration
• Automation
• Cloud Environments