Digital Workplace Engineer IV

Capital Group•Charlotte, NC

3d•Hybrid

About The Position

As a Digital Workplace Engineer IV focused on Enterprise Artificial Intelligence, you will serve as a senior technical leader responsible for designing, implementing, and governing how enterprise AI solutions connect to Capital Group's systems, data, and business processes. You will play a critical role in extending Microsoft Copilot Studio, Azure AI Foundry, and the broader Microsoft AI ecosystem through secure integrations with internal and third-party platforms. You will provide technical leadership for enterprise AI connectivity patterns, including APIs, data connectors, retrieval architectures, Model Context Protocol (MCP) integrations, external knowledge sources, workflow automation, and agent-to-agent interactions. You will help establish reusable engineering foundations that enable product teams and business partners to safely accelerate AI adoption across the firm. In this role, you will partner closely with application development teams, product teams, architecture, information security, legal, compliance, privacy, and data teams to deliver sophisticated agentic solutions that address real business challenges while adhering to enterprise governance standards. You will serve as a subject matter expert and trusted advisor for teams seeking to leverage artificial intelligence, helping them navigate technical complexity, evaluate architecture options, and implement scalable patterns. As a senior engineer, you will lead the most complex implementations, contribute to technology strategy and roadmaps, mentor other engineers, and help shape the future of Capital Group's enterprise AI ecosystem.

Requirements

Extensive experience designing and implementing enterprise technology solutions in complex and highly regulated environments.
Deep expertise with Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, Power Platform, Microsoft Graph, and related Microsoft cloud technologies.
Strong experience integrating enterprise platforms with internal and third-party applications through APIs, connectors, web services, event architectures, and emerging standards such as Model Context Protocol (MCP).
Experience architecting and delivering custom AI agents, orchestrations, copilots, workflow automations, and retrieval-based solutions that leverage enterprise knowledge and data.
Understanding of grounding strategies, retrieval architectures, vector-based knowledge systems, prompt engineering, evaluation frameworks, and responsible AI practices.
Experience partnering with application teams to translate business requirements into scalable AI-enabled solutions.
Demonstrated success working with Information Security, Legal, Privacy, Risk, and Compliance teams to implement enterprise capabilities that satisfy governance and regulatory requirements.
Ability to lead technical discussions across organizational boundaries and effectively communicate complex concepts to both technical and business stakeholders.
Enjoy mentoring engineers and helping teams adopt engineering best practices, reusable architectures, and operational excellence.
Continuously evaluate emerging AI technologies and industry trends to identify opportunities that create measurable business value.
8+ years of experience working in engineering technologies.

Responsibilities

Designing and implementing enterprise AI integration architectures that connect Microsoft Copilot and AI platforms to internal and external applications.
Building custom agents and orchestrations using Copilot Studio, Azure AI Foundry, Power Platform, Microsoft Graph, APIs, connectors, and enterprise knowledge repositories.
Developing reusable enterprise patterns for AI connectivity, retrieval, workflow automation, agent interoperability, and external system integration.
Enabling secure access to enterprise and third-party data sources while maintaining security, privacy, compliance, and governance requirements.
Creating and operationalizing custom connectors, API integrations, MCP servers, and service-to-service communication architectures.
Partnering with application and product teams to deliver complex AI use cases from design through deployment and operational support.
Evaluating platform capabilities, solution architectures, and integration approaches to determine the most appropriate implementation strategy.
Establishing monitoring, observability, telemetry, performance standards, and operational readiness processes for AI-enabled solutions.
Supporting AI governance activities including model evaluation, solution reviews, responsible AI controls, and risk assessments.
Implementing CI/CD, environment management, and application lifecycle management practices for Copilot Studio, AI Foundry, and Power Platform solutions.
Conducting proof-of-concepts, vendor evaluations, and technology assessments for emerging AI capabilities and external platforms.
Providing technical leadership on large-scale, enterprise initiatives involving multiple application teams, technologies, and business stakeholders.
Mentoring engineers and citizen developers on enterprise AI architecture, engineering standards, integration patterns, and operational practices.
Driving innovation through experimentation while maintaining a strong focus on reliability, security, scalability, and business value realization.