Principal AI Platform Engineer

🔥 6 minutes ago

🏈 Alabama – Remote

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💵 $139.7k - $232.9k / year

⏰ Full Time

🔴 Lead

🏗️ Platform Engineer

👻 Ghost score 0%

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Logo of M&T Bank

M&T Bank

10,000+ employees

Founded 1856

🛡️ Insurance

💼 Consulting

🏦 Banking

Insurance • Consulting • Banking

M&T Bank is a leading regional financial institution that provides a wide range of banking services to personal, business, and commercial clients. Known for its customer satisfaction in mobile banking, M&T Bank offers products and services such as checking accounts, credit cards, mortgages, personal loans, and insurance. Additionally, it provides financial planning through Wilmington Advisors @ M&T. The bank is committed to community engagement, supporting local businesses, multicultural banking, and volunteerism. With a focus on cybersecurity and digital banking solutions, M&T Bank serves its clientele through comprehensive online and mobile services.

📋 Description

• Design, develop, and support enterprise-scale GenAI solutions, including AI-assisted development, documentation, testing, analytics, and workflow automation • Lead architecture, implementation, and optimization of Retrieval-Augmented Generation (RAG) solutions, including ingestion pipelines, embeddings, vector stores, retrieval frameworks, and search capabilities • Design, review, and approve agent-based and tool-integrated AI architectures, including multi-step LLM workflows • Develop and oversee APIs, shared services, and reusable frameworks connecting AI models to internal systems, platforms, and approved third-party tools • Establish prompt engineering standards, evaluation methodologies, and testing frameworks • Drive model testing, benchmarking, evaluation, and performance analysis using approved frameworks and governance standards • Author secure, scalable, maintainable code using Java, Python, and C#, while promoting engineering excellence • Lead technical discussions with Product Managers, Architects, Engineers, and senior stakeholders to translate business objectives into enterprise-scale AI solutions • Serve as a subject matter expert for Generative AI, AI platform engineering, and responsible AI practices • Mentor and coach engineers on software engineering, AI architecture patterns, algorithms, data structures, and enterprise platform design • Contribute to technical roadmaps balancing strategic AI initiatives, platform modernization, innovation, operational excellence, and technical debt reduction • Define and champion architecture standards, design patterns, and implementation guidance for AI-enabled solutions • Apply engineering, operational, and AI performance metrics to identify process improvements and platform optimization opportunities • Lead resiliency, performance, observability, and security best practices within AI platforms and services • Drive responsible AI, model governance, security, compliance, privacy, and risk management throughout the AI development lifecycle • Participate in and present to enterprise architecture forums, engineering councils, and leadership committees • Adhere to company risk and regulatory standards, policies, controls, and Risk Appetite; escalate risk-related issues • Maintain internal control standards and implement internal/external audit and regulatory findings as applicable • Complete other related duties as assigned

🎯 Requirements

• Associate’s degree and a minimum of 9 years’ systems analysis and/or application development work experience, or Bachelor's degree and a minimum of 7 years’ systems analysis and/or application development work experience • In lieu of a degree, a combined minimum of 11 years’ education and/or relevant work experience, including a minimum of 7 years’ systems analysis and/or application development work experience • Expert proficiency in a minimum of 1 relevant programming language and advanced proficiency in a minimum of 1 additional relevant programming language • Strong foundation in software engineering principles, data structures, algorithms, and distributed system design • Hands-on experience developing production applications using Java, Python, C#, or other modern enterprise programming languages • Experience designing and integrating RESTful APIs, microservices, and API-driven architectures • Advanced knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, and AI application development • Experience building and supporting AI-enabled applications within enterprise SDLC, security, compliance, and governance frameworks • Proven ability to influence technical direction, engineering standards, and architectural decisions across multiple teams • Preferred: experience implementing enterprise Generative AI solutions within financial services or other highly regulated industries • Preferred: expertise in Retrieval-Augmented Generation (RAG), embeddings, vector databases, retrieval frameworks, and semantic search technologies • Preferred: understanding of Transformer architectures, attention mechanisms, tokenization strategies, and model evaluation techniques • Preferred: experience designing AI agents, tool-integrated workflows, and advanced LLM orchestration frameworks • Preferred: expertise with Microsoft Azure, Azure AI Services, OpenAI technologies, and cloud-native AI platforms • Preferred: experience establishing enterprise AI governance, responsible AI practices, and model risk management controls • Preferred: experience leading large-scale technical initiatives, platform modernization efforts, or enterprise capability rollouts • Preferred: experience influencing senior technology and business stakeholders and driving enterprise-wide adoption of new technologies • Preferred: ability to work autonomously while leading complex technical initiatives across multiple teams • Preferred: advanced verbal and written communication skills with the ability to present complex technical concepts to executive audiences • Preferred: subject matter expertise in AI platform engineering, software architecture, and enterprise application development • Preferred: experience with CI/CD pipelines, DevOps tooling, automated testing, observability, and platform reliability engineering practices

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