Microsoft Ai & Automation Engineer - Productivity Intelligence (Financial Services) | Hoboken, NJ, USA

Microsoft Ai & Automation Engineer - Productivity Intelligence (Financial Services)

{"description": " Do you want your voice heard and your actions to count?

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world's leading financial groups. Across the globe, we're 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world's most trusted financial group, it's part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

Role Summary

This role is responsible for enabling enterprise-wide adoption of Microsoft Copilot, Copilot Studio, and Power Platform AI capabilities across a large, highly regulated financial institution operating multiple Microsoft 365 tenants. The focus is on building scalable platforms, governance frameworks, and reusable architectural patterns that empower business teams and citizen developers to safely leverage AI-rather than delivering isolated, one-off solutions.

The ideal candidate blends deep technical expertise in the Microsoft AI ecosystem with strong platform architecture and strategic leadership skills, and brings a clear vision for evolving from Copilot-driven productivity use cases to advanced, code-first AI solution development using Azure AI Foundry.

Key Responsibilities

Platform Strategy & Enterprise Architecture

• Contribute to the definition and execution of the enterprise strategy for Microsoft Copilot, Copilot Studio, and Power Platform, ensuring alignment with business goals, security standards, and financial services regulatory requirements.

• Drive architecture decisions related to Dataverse, system integrations, security models, environment strategy, scalability, and performance.

• Partner with Enterprise Architecture to define reusable patterns, shared components, libraries, and scalable solution architectures.

• Establish platform standards, governance models, and Application Lifecycle Management (ALM) practices to enable consistent, secure delivery of AI-powered solutions across the organization. Copilot Studio Agent Development & Enablement

• Design, build, test, deploy, and manage Copilot Studio agents aligned to business processes and user needs.

• Implement actions, orchestration, and workflows using Power Automate, structured knowledge sources, and governed enterprise data access.

• Build and refine conversational flows, topics, orchestrations, and generative answers to ensure accuracy, usability, and safe enterprise adoption.

• Integrate Copilot agents with Microsoft Graph, Dataverse, SharePoint, and other enterprise systems to deliver context-aware AI experiences.

Power Platform Architecture & Automation

• Design and develop complex Power Automate workflows, including approvals, exception handling, retries, orchestration patterns, and operational monitoring.

• Build and manage integrations across Microsoft 365, Dataverse, SharePoint, and external systems using standard and custom connectors.

• Create reusable enterprise components and patterns (e.g., approvals, notifications, routing, data updates, error handling).

• Support secure authentication and authorization configurations, including OAuth, app registrations, service principals, and API connections.

Azure AI Foundry & Advanced AI Solutions

• Define governance and architectural approaches for future deployment of workflow-based and autonomous agents using Azure AI Foundry.

• Build production-grade agents using the Azure AI Foundry SDK (Python, C#, or TypeScript).

• Define agent behavior, memory, tools, and reasoning workflows to support intelligent, task-driven automation.

• Implement retrieval-augmented generation (RAG) pipelines using vector databases for domain-specific knowledge retrieval.

• Bridge low-code Copilot Studio solutions with advanced, code-first Azure AI Foundry capabilities to mature the organization's AI development lifecycle over time.

API Integration & Data Connectivity

• Build and consume RESTful APIs and implement tool calling and service orchestration for AI agents.

• Connect AI solutions to enterprise data sources and APIs to enable real-time information retrieval and context-rich automation.

• Extend Power Platform capabilities using Azure services such as Azure Functions and Logic Apps where appropriate.

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