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

MUFG•Tampa, FL

1d•Hybrid

About The Position

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.

Requirements

5–8+ years of experience delivering business applications and automation solutions, including 3–5+ years with the Microsoft Power Platform.
2+ years of hands‑on experience building agents in Microsoft Copilot Studio, including conversation design and orchestration.
Strong programming skills in Python, C#, or JavaScript, with experience building and consuming RESTful APIs.
Experience with Azure cloud services and AI workloads, including Azure AI Foundry, Azure OpenAI, and Azure AI Search.
Deep knowledge of Dataverse data modeling, security roles, relationships, and enterprise integrations.
Solid understanding of LLMs, prompt engineering, RAG, and vector search techniques within the Microsoft ecosystem.
Proven ability to lead technical design, establish standards, and operate independently in a large enterprise.
Strong stakeholder communication skills with both technical and non‑technical audiences.
Experience in financial services or other highly regulated environments.
Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of formal education and experience.

Nice To Haves

2+ years building AI agents using Copilot Studio and Azure AI Foundry.
Experience with agentic frameworks such as Semantic Kernel, AutoGen, or Agent Development Kit (ADK).
Familiarity with Microsoft Purview and Responsible AI compliance tooling.
Experience with CI/CD pipelines using Azure DevOps or GitHub Actions.
Knowledge of enterprise Responsible AI governance processes.
Microsoft certifications (PL‑400, PL‑600, AI‑102, AZ‑305).
Demonstrated leadership in piloting or scaling AI and automation solutions.
Lean / Agile delivery experience.

Responsibilities

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.
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.
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.
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.
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.
Collaborate with governance, security, risk, and compliance teams to ensure alignment with enterprise and regulatory standards.
Design and deliver solutions that adhere to governance policies, including environment strategy, data loss prevention (DLP), solution packaging, and deployment controls.
Ensure AI solutions comply with Responsible AI principles and enterprise AI usage policies, positioning Copilot as a decision‑support tool rather than a decision‑maker.
Implement guardrails such as content filtering, audit logging, user consent flows, and required governance documentation (use‑case descriptions, risk assessments, approvals).
Develop and maintain best‑practice templates, reusable assets, training materials, and standards that enable safe citizen development at scale.
Mentor developers, power users, and business teams on Copilot Studio and Power Platform capabilities.
Partner with AI Adoption, training, and champions programs to drive broad, responsible Copilot adoption.
Participate in workshops to assess current‑state processes, identify pain points, and prioritize high‑value Copilot use cases that improve productivity, decision‑making, and operational efficiency.
Define and track KPIs for Copilot adoption and outcomes, including productivity gains, quality improvements, user satisfaction, and ROI.
Monitor agent performance and continuously refine solutions based on analytics and user feedback.
Stay current with emerging Microsoft AI capabilities and evaluate their potential impact and value to the enterprise.
Contribute to technical documentation, design artifacts, and solution best practices.