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Capital Group

Asset management with long-term portfolios

Digital Workplace Engineer 4, Enterprise AI

AI Application EngineeringUpdated on Nov 13
Full-timeCharlotte, NC, USA$136.7k - $218.8kIn-person

About the Job

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 standards such as Model Context Protocol (MCP).
  • Experience architecting and delivering custom AI agents, orchestrations, copilots, workflow automations, and retrieval-based solutions using 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 meeting governance and regulatory requirements.
  • Ability to lead technical discussions across organizational boundaries and communicate complex concepts to technical and business stakeholders.
  • At least 8 years of experience working in engineering technologies.
  • Familiarity with designing and implementing enterprise AI integration architectures that connect Microsoft Copilot and AI platforms to internal and external applications.
  • Familiarity with building custom agents and orchestrations using Copilot Studio, Azure AI Foundry, Power Platform, Microsoft Graph, APIs, connectors, and enterprise knowledge repositories.
  • Familiarity with developing reusable enterprise patterns for AI connectivity, retrieval, workflow automation, agent interoperability, and external system integration.
  • Familiarity with enabling secure access to enterprise and third-party data sources while maintaining security, privacy, compliance, and governance requirements.
  • Familiarity with creating and operationalizing custom connectors, API integrations, MCP servers, and service-to-service communication architectures.
  • Familiarity with partnering with application and product teams to deliver complex AI use cases from design through deployment and operational support.
  • Familiarity with evaluating platform capabilities, solution architectures, and integration approaches to determine appropriate implementation strategies.
  • Familiarity with establishing monitoring, observability, telemetry, performance standards, and operational readiness processes for AI-enabled solutions.
  • Familiarity with supporting AI governance activities, including model evaluation, solution reviews, responsible AI controls, and risk assessments.
  • Familiarity with implementing CI/CD, environment management, and application lifecycle management practices for Copilot Studio, AI Foundry, and Power Platform solutions.
  • Familiarity with conducting proof-of-concepts, vendor evaluations, and technology assessments for emerging AI capabilities and external platforms.
  • Familiarity with providing technical leadership on large-scale enterprise initiatives involving multiple application teams, technologies, and business stakeholders.
  • Familiarity with mentoring engineers and citizen developers on enterprise AI architecture, engineering standards, integration patterns, and operational practices.
  • Familiarity with driving innovation through experimentation while maintaining reliability, security, scalability, and business value realization.

Responsibilities

  • Design, implement, and govern how enterprise AI solutions connect to company systems, data, and business processes.
  • Extend Microsoft Copilot Studio, Azure AI Foundry, and the broader Microsoft AI ecosystem through secure integrations with internal and third-party platforms.
  • Provide technical leadership for enterprise AI connectivity patterns, including APIs, data connectors, retrieval architectures, MCP integrations, external knowledge sources, workflow automation, and agent-to-agent interactions.
  • Establish reusable engineering foundations that enable product teams and business partners to accelerate AI adoption safely.
  • Partner with application development, product, architecture, information security, legal, compliance, privacy, and data teams to deliver agentic solutions that meet enterprise governance standards.
  • Serve as a subject matter expert and trusted advisor, helping teams navigate technical complexity, evaluate architecture options, and implement scalable patterns.
  • Lead the most complex implementations and contribute to technology strategy and roadmaps.
  • Mentor engineers and help shape the enterprise AI ecosystem.
  • Continuously evaluate emerging AI technologies and industry trends to identify opportunities that create measurable business value.

About the Company

Capital Group

Asset management with long-term portfolios

Capital Group is a private investment firm managing equity and fixed-income assets for millions of investors. It builds long-term, high-conviction portfolios using rigorous research and the American Funds lineup to pursue steady, durable results rather than short-term trades. It differentiates itself through strong personal accountability, a globally distributed team, and a research-driven investment process. Its goal is to improve people’s lives through successful investing.

Company size
5,001-10,000
Company stage
Not listed
Total funding
$65.4B
Headquarters
Dongcheng District, China
Founded
Not listed

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