What you\'ll do:The Enterprise AI Engineer is a high-impact, highly visible role at the intersection of artificial intelligence, business strategy, and hands-on technical execution. This is a field-facing, mission-critical role for engineers who think like founders and operate like consultants. In this role, you won\'t just be building technology for the bank; you\'ll be working side by side with engineers from our strategic partners, such as OpenAI & ElevenLabs.
The Enterprise AI Engineer will be a member of a central team fully focused on delivering automation & AI-powered solutions that solve real problems and create measurable impact. You will partner with business units and functional areas to understand complex challenges, design and build production-grade AI and automation workflows, and implement scalable systems and elevated capability.
This role demands a rare combination: deep technical acuity, executive presence, and the instinct to translate ambiguous business needs into working solutions.
Key ResponsibilitiesBusiness Solutioning, Engineering & Delivery- Embed within business functions across the institution to identify, scope, and deliver automation and AI-enabled solutions that address 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.
- Lead 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.
What do you need?- 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 (Nice to Haves)- 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.
Technology Skills- Proficiency in Python and JavaScript/TypeScript for full-stack AI development.
- Experience with LLM orchestration frameworks and API-based model deployment.
- Familiarity with cloud platforms (AWS, Azure, or GCP)
- Proficiency in Microsoft Office applications (Word, Excel, PowerPoint, Outlook) for executive communication and documentation.
- Experience with project management and collaboration tools such as Jira, Confluence, SharePoint, or similar platforms.
