Generative AI is making machine learning model development faster than ever. Be a change agent and join the Chase team that takes advantage of generative AI to reduce model governance friction and liberate the true value of AI.
As an AI ML Governance & Automation Lead in Consumer & Community Banking Digital AI/ML, you will drive the successful delivery of complex technology and governance programs that enable responsible innovation across advanced AI/ML use cases, leveraging your deep knowledge of technical program management, Model Development Lifecycle, and governance frameworks, you will partner with data scientists, engineers, product teams, risk partners, and business stakeholders to develop scalable solutions that reduce friction in the model lifecycle while maintaining strong controls. Your analytical reasoning, adaptability, and ability to navigate ambiguity will be essential as you help define new operating models for agentic, generative, and customer-facing AI solutions. With advanced communication and stakeholder management skills, you will influence decision-making, align cross-functional teams, and ensure technology initiatives meet both business objectives and governance expectations. As a subject matter expert, you will contribute to operational plans, risk mitigation strategies, and process improvements that enable faster, safer, and more consistent AI/ML delivery.
Job responsibilities
- Develop and execute comprehensive program plans to accelerate AI/ML model governance, incorporating technical requirements, governance milestones, resource allocation, dependencies, and delivery timelines.
- Partner with data science, engineering, product, legal, risk, controls, compliance, and business stakeholders to define program scope, objectives, deliverables, and success measures for advanced AI/ML governance initiatives.
- Design and implement scalable governance solutions for agentic, generative, and customer-facing AI/ML use cases, helping reduce bottlenecks across the model development and approval lifecycle.
- Identify, assess, and mitigate program risks, proactively addressing roadblocks and implementing contingency plans to maintain delivery momentum.
- Translate complex business, technical, model risk, and operational requirements into actionable plans, milestones, and execution activities.
- Drive cross-functional alignment on governance standards, controls, documentation, and operating procedures for emerging AI/ML capabilities.
- Utilize advanced analytical reasoning to evaluate program performance, identify process inefficiencies, and implement data-driven improvements that enhance speed, consistency, and quality.
- Champion agile delivery practices, continuous improvement, and responsible AI innovation across the team.
- Communicate program status, risks, decisions, and dependencies clearly to senior stakeholders, ensuring transparency and timely escalation where needed.
- Contribute to the development of repeatable frameworks, playbooks, and governance patterns that support scalable AI/ML delivery across CCB Digital.
Required qualifications, capabilities, and skills
- 5+ years of experience or equivalent expertise in technical program management, leading complex technology, data, AI/ML, risk, or governance programs in a large organization.
- Strong understanding of AI/ML development lifecycles, model governance, model risk management, or related control processes.
- Advanced stakeholder management skills, with the ability to establish productive working relationships and influence decision-making across engineering, data science, product, risk, and business teams.
- Proven ability to manage complex, cross-functional programs with multiple dependencies, competing priorities, and evolving requirements.
- Demonstrated proficiency in analytical reasoning and problem solving, with the ability to break down complex business, technical, risk, and operational objectives into actionable plans.
- Experience driving process improvement, operating model design, or governance transformation in a fast-paced technology environment.
- Strong communication skills, including the ability to clearly articulate complex technical and governance topics to both technical and non-technical audiences.
- Proven track record of managing resources, timelines, risks, and deliverables in an agile environment.
- Ability to navigate ambiguity, drive structure, and deliver outcomes in emerging or rapidly evolving technology areas.
Preferred qualifications, capabilities, and skills
- Experience with generative AI, agentic AI, large language models, or customer-facing AI/ML solutions.
- Familiarity with responsible AI principles, model validation, model monitoring, AI controls, or regulatory expectations related to AI/ML.
- Understanding of data management, data governance processes, and related tools.
- Experience working in financial services, consumer banking, digital product organizations, or highly regulated environments.
- Experience using approved generative AI tools to design, prototype, or build solutions that automate governance processes, generate required governance artifacts, and improve efficiency across the AI/ML model lifecycle.