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.

Location

Buffalo, New York, United States of America