About The Role

This role sits at the intersection of business strategy, AI innovation, and execution. Embedded within a business line, you'll identify opportunities, design and develop AI solutions, navigate enterprise governance processes, and lead implementations through production deployment. You will own outcomes end-to-end, serving as the critical link between business demand and governed, scalable AI solutions that create measurable impact.

Skills and Indicators

Business fluency: You can sit in a room with a Commercial Banking RM or a Risk Officer and understand their problem in their language. You translate it into an AI solution design, not the other way around.
Delivery ownership: You do not hand off. You own the use case from problem statement through production adoption. If it stalls in governance, you unstick it. If adoption lags, you fix it.
Builder mentality: You prototype fast, iterate with stakeholders, and ship governed solutions. You are not a consultant who writes a deck and leaves.
Pattern thinking: Every use case you deliver produces a reusable pattern for the next one. You document what works and feed it back to the hub.

Required Qualifications

Associate’s degree and a minimum of 7 years’ systems analysis and/or application development work experience or Bachelor's degree and a minimum of 5 years' systems analysis and/or application development work experience. In lieu of a degree, a combined minimum of 9 year’s education and/or relevant work experience, including a minimum of 5 years’ system analysis and/or application development work experience.
5+ years in software engineering, applied AI, or solutions engineering. You have shipped production software, not just prototypes.
Hands-on experience building applications that use LLMs or foundation models (prompt engineering, RAG pipelines, agent frameworks, tool calling). You have built at least one system that calls a model in production.
Experience working directly with business stakeholders to translate a problem into a technical solution. You can run a discovery session, not just take a requirements document.
Ability to work across the full stack: API integration, data pipeline, model integration, front-end or workflow integration. You are not specialized in one layer.
Comfort with governance and compliance processes. You navigate risk reviews and architecture approvals as part of delivery, not as obstacles.

Preferred Qualifications

Experience in financial services, banking, or another regulated industry. You understand why governance exists and can work within it productively.
Experience with agentic AI patterns: multi-step workflows, tool use, autonomous execution with guardrails.
Familiarity with the M&T AI platform stack (Azure AI Foundry, Anthropic Claude, Azure APIM) or comparable enterprise AI platforms.
Experience mentoring or training others on AI delivery practices. As the hub-and-spoke model scales, FDEs train divisional engineers.

M&T Bank is committed to fair, competitive, and market-informed pay for our employees. The pay range for this position is $116,400.00 - $194,000.00 Annual (USD). The successful candidate’s particular combination of knowledge, skills, and experience will inform their specific compensation.