Enterprise AI Engineer

About the role

The Enterprise AI Engineer plays a pivotal role at Customers Bank, bridging the gap between artificial intelligence, business strategy, and hands-on technical execution. This role requires a unique blend of deep technical acumen, executive presence, and the ability to translate complex business needs into actionable solutions.

Responsibilities

• Embed within business functions to identify, scope, and deliver automation and AI-enabled solutions addressing high-priority operational and strategic challenges.
• Translate complex, ambiguous business problems into structured technical requirements and delivery plans.
• Lead end-to-end project delivery from discovery and prototyping through production deployment and adoption, maintaining clear accountability at each stage.
• Build production-ready solutions with strong engineering fundamentals: reliability, observability, security, and scalability.
• Write, review, and ship code across the stack using Python, JavaScript/TypeScript, or comparable languages.
• Integrate AI capabilities with core banking platforms, data infrastructure, and third-party systems via APIs and data pipelines.
• Ensure AI systems meet model risk management standards, data governance policies, and applicable regulatory expectations.

Stakeholder Engagement & Change Leadership

• Develop playbooks, reusable components, and implementation patterns that accelerate future AI deployments across the institution.
• Represent AI capabilities and implementation insights in executive and governance forums as needed.
• Build trusted relationships with senior business leaders, risk officers, operations leaders, and technology teams across the institution.
• Communicate complex technical concepts clearly and compellingly to non-technical audiences, adapting messaging to the audience.
• Led change management and adoption efforts to ensure AI solutions are embedded, understood, and sustained within business teams.
• Facilitate working sessions, stakeholder reviews, and demos that drive alignment and accelerate decision-making.

AI Governance, Risk & Regulatory Alignment

• Ensure deployed AI systems are developed and maintained in accordance with the Bank's AI governance framework, model risk management standards, and applicable regulatory guidance (OCC, FFIEC, FinCEN).
• Coordinate with Model Risk Management, Compliance, Legal, and Audit teams to support reviews, validations, and documentation of AI systems.
• Maintain accurate records for AI model inventories, governance logs, and deployment documentation.
• Monitor and communicate emerging regulatory developments related to AI/ML use in financial services.
• Identify risks in AI systems early and surface them through appropriate governance channels with recommended mitigations.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, Data Science, or a related technical field; advanced degree a plus.
• Minimum 4+ years of experience in software engineering, AI/ML engineering, technical deployment, or a related field, including demonstrated customer- or business-facing delivery.
• Proven ability to build and ship production-grade AI systems using LLMs / generative AI.
• Strong full-stack engineering proficiency with Python, JavaScript/TypeScript, or comparable languages.
• Demonstrated ability to scope complex technical projects, drive delivery in ambiguous environments, and manage competing priorities without losing momentum.
• Outstanding communication skills: able to engage C-suite stakeholders and technical engineers with equal fluency.
• High degree of intellectual curiosity and a growth mindset — you actively seek out what you don’t know and close those gaps fast.
• Ability and willingness to travel to business unit sites across the institution and to key external engagements as needed.

Preferred Qualifications

• Experience working in regulated industries — financial services, healthcare, or government — with an understanding of compliance and risk considerations in AI deployment.
• Familiarity with banking operations, risk management, BSA/AML processes, or financial crimes compliance functions.
• Background in data engineering or platform engineering in cloud environments (AWS, Azure, or GCP).
• Experience working in a forward-deployed, consulting, or embedded engineering capacity with business clients.
• Exposure to enterprise AI governance frameworks, model risk management, or responsible AI practices.
• Professional certifications in AI/ML, cloud architecture, or project management are a plus.