Role Summary

The Lead AI Platform Engineer is a hands‑on technical contributor responsible for designing, developing, and integrating Generative AI–enabled capabilities within M&T Bank’s secure, governed enterprise environment. This role combines strong software engineering fundamentals with applied GenAI experience and partners closely with product, architecture, and engineering teams to deliver scalable, reliable, and responsible AI solutions.

Key Responsibilities

• Design, develop, and support GenAI‑enabled features including AI‑assisted coding, documentation, testing, analysis, and workflow automation

• Implement and maintain retrieval‑augmented generation (RAG) solutions, including data ingestion, embeddings, vector stores, and search pipelines

• Design and build agent‑based and tool‑invoking GenAI workflows, including multi‑step LLM interactions using approved enterprise platforms

• Develop and integrate APIs and backend services connecting LLMs to internal systems and approved third‑party tools

• Lead prompt design, testing, and iteration to improve output quality, relevance, and safety

• Participate in model testing, evaluation, and performance analysis using established enterprise frameworks

• Contribute hands‑on development using modern languages and frameworks (e.g., Java, Python, C#)

• Collaborate with Product Managers, Architects, and Engineers to translate requirements into technical solutions

• Provide technical guidance and mentoring to less experienced engineers

• Follow and promote M&T Bank SDLC, security, and responsible AI standards

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.

• Strong foundation in software engineering principles, data structures, and algorithms

• Hands‑on experience with Java, Python, or C# in production environments

• Experience with RESTful APIs, API‑driven development, and Git‑based version control

• Working knowledge of machine learning and large language model (LLM) fundamentals

• Experience working within enterprise SDLC, security, and compliance standards

Preferred Qualifications

• Experience implementing Generative AI solutions in enterprise or regulated environments

• Hands‑on experience with RAG architectures, embeddings, and vector databases

• Familiarity with Transformer‑based models, attention mechanisms, and tokenization

• Experience with Microsoft Azure, including Azure‑based AI services and GenAI platforms

• Exposure to CI/CD pipelines, DevOps tooling, and automated testing

• Understanding of responsible AI, data privacy, and model governance principles

Location