Principal AI Platform Engineer

M&T Bank

. Design, develop, and support enterprise-scale GenAI solutions, including AI-assisted development, documentation, testing, analytics, and workflow automation .

Posted 10/2/2026full-timeRemote • Alabama • United StatesLead💰 $139,700 - $232,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Generative AI solutions, including architecture, implementation, and optimization of Retrieval-Augmented Generation (RAG) systems. Proficient in programming languages such as Java, Python, and C#, with a strong foundation in software engineering principles and AI governance practices.

Highest-signal resume keywords

Generative AI ExpertiseRetrieval-Augmented Generation (RAG)Java ProgrammingPython ProgrammingAPI Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

JavaPythonC#RESTful API DesignMicroservices ArchitecturePrompt EngineeringData StructuresAlgorithmsDistributed System DesignAI Application Development

Soft Skills

Advanced Communication SkillsMentoringInfluencing Technical DirectionCollaborationLeadership

Tools & Technologies

Microsoft AzureAzure AI ServicesOpenAI TechnologiesCI/CD PipelinesDevOps ToolingAutomated TestingObservability ToolsPlatform Reliability Engineering

Industry Keywords

Enterprise AI SolutionsAI GovernanceModel Risk ManagementComplianceSecurity Standards

Tech Stack

Tools & technologies

AzureCloudJavaMicroservicesPythonSDLC

About the role

Key responsibilities & impact

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

What you’ll need

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