The Role
Lead the architecture, implementation, and operation of an enterprise technology metrics platform. Build integrations, scalable data pipelines, metric calculation engines, dashboards, and governance to standardize reporting across systems (Jira, ServiceNow, GitLab, Snowflake, Power BI). Enable near real-time reporting, data quality controls, automated monthly reporting, executive visualizations, and mentor engineering teams.
Summary Generated by Built In
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.
Skills Required
- Bachelor's degree plus minimum 5 years systems analysis and/or application development experience OR Associate's degree plus minimum 7 years OR in lieu of degree a combined minimum of 9 years education/work experience including 5 years systems analysis/application development
- Experience as a Lead Engineer, Data Engineer, Analytics Engineer, Software Engineer, Solution Architect, or similar role
- Strong experience designing enterprise reporting platforms and analytics architectures
- Experience building integrations using APIs, ETL/ELT pipelines, event-driven architectures, and enterprise data platforms
- Experience with Power BI, SQL, dashboard engineering, reporting automation, and data visualization technologies
- Strong software engineering and solution architecture experience
- Experience working with large-scale enterprise data environments
- Ability to translate business requirements into scalable technical solutions
- Strong stakeholder engagement and technical leadership skills
M&T Bank Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about M&T Bank and has not been reviewed or approved by M&T Bank.
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Retirement Support — Retirement benefits are positioned as a strong pillar, including a 401(k) match and the possibility of an additional employer contribution, plus access to an employee stock purchase plan.
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Leave & Time Off Breadth — Time-off offerings are framed as competitive, with a flexible PTO approach and paid volunteer time called out as a meaningful add-on to standard leave.
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Wellbeing & Lifestyle Benefits — Wellbeing support appears comparatively robust, highlighted by mental-health therapy/coaching sessions and broader wellness programming alongside community-oriented perks.
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The Company
What We Do
M&T Bank is a multi-state community-focused bank serving New York, Maryland, New Jersey, Pennsylvania, Delaware, Connecticut, Virginia, West Virginia and Washington, D.C. Founded in 1856, the company provides banking, investment, insurance and mortgage financial services to more than 3.6 million consumer, business and government clients.
