Principal Legal & Regulatory Strategist AI Operations

Overview

We have partnered with our client in their search for a Principal Legal & Regulatory Strategist for AI Operations

• Process Engineering:
  Expertise in "outcome-back" redesign of complex operational workflows.
• AI/ML Mastery:
  Deep technical knowledge of LLMs, RAG, and MLOps (ideally in GCP).
• Regulatory Fluency:
  Experience navigating financial compliance (FCRA, GLBA) and AI governance.
• End-to-End Execution:
  Ability to lead high-priority AI initiatives from business case to production.
• Strategic Leadership:
  Influencing cross-functional senior stakeholders to drive ROI-focused transformation.

• Process Re-engineering:
  Gain deep understanding of operational processes (including regulated processes) to identify transformation opportunities and effectively redesign them using a right-to-left methodology starting with the desired result.
• End-to-End Execution:
  Lead the lifecycle of high-priority AI initiatives from initial business case and technical feasibility to production-grade deployment within Operations
• Cross-Functional Orchestration:
  Serve as the primary technical interface between Operations, Technology, Data & Analytics, Compliance, and other stakeholders to ensure AI solutions are performing as expected, scalable, and compliant. Drive alignment across senior stakeholders and technical teams to prioritize AI roadmaps that deliver the highest ROI and operational uplift.
• Performance and ROI Benchmarking:
  Establish rigorous KPIs for AI solutions, tracking model accuracy, cost, quality, speed, and scalability metrics to prove business value.
• AI Governance Integration:
  Embed "Responsible AI" protocols into the delivery process, ensuring all deployments meet stringent financial services standards for explainability, bias mitigation, and data lineage

Technical

Qualifications:

• AI/ML Proficiency:
  Deep understanding of Large Language Model (LLM) architectures, Retrieval-Augmented Generation (RAG), and the nuances of fine-tuning models for specific domain expertise.
• Infrastructure and MLOps:
  Proven experience deploying models within cloud environments (GCP preferred) and a strong grasp of MLOps principles (CI/CD for ML, model monitoring, and versioning).
• Data Pipelines:
  Proficiency in working with complex data architectures, multi-system integrations, and real-time streaming data. Operational and Strategic Qualifications
• Financial Services Regulatory Expertise:
  Strong working knowledge of global financial regulations impacting AI, including FCRA, GLBA, and privacy regulations/frameworks.
• Process Design Expertise:
  Demonstrated ability to quickly understand and reimagine complex processes using modern technology.
• Change Management:
  Proven track record of leading high-impact digital transformations within complex organizations.

• Bachelor's or Master's degree in Computer Science, Engineering, Finance, or a related field; MBA, relevant professional degree, or equivalent strategic experience is a plus.

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