Lead AI Platform Engineer
Indexed description
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
- 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
- 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
Buffalo, New York, United States of America
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