AI Senior Manager, AI Engineering

Capital Group•Charlotte, NC

15h•Hybrid

About The Position

As the AI Senior Manager for AI Engineering, you will help translate Capital Group’s AI-first operating model into practical transformation across investment systems. Reporting to the AI Engineering Director, you will lead teams focused on smart automation, AI-enabled design, agentic delivery patterns, and measurable operational improvement. This role is hands-on and execution oriented. You will partner with product, engineering, operations, data, architecture, cybersecurity, risk, and compliance teams to identify high-value opportunities, deliver manageable MVPs, and scale human-plus-agent capabilities that reduce manual work, improve straight-through processing, strengthen exception management, and increase delivery quality.

Requirements

8+ years of enterprise technology experience, including 3+ years leading teams or programs across AI engineering, process transformation, data engineering, platform engineering, testing, or investment systems technology.
5+ years of proven people leadership experience building, coaching, and leading high-performing engineering teams, including engineers, managers, automation specialists, workflow analysts, and cross-functional delivery teams.
Experience delivering AI-enabled workflow solutions, business process modernization, or human-plus-agent operating patterns in a complex enterprise environment.
Strong understanding of investment systems, financial services workflows, regulated processes, or equivalent mission-critical enterprise domains.
Working knowledge of generative AI, agentic AI, orchestration, RAG, prompt patterns, evaluations, observability, guardrails, automation platforms, APIs, and modern engineering practices.
Experience partnering with data, platform, architecture, cybersecurity, risk, legal, compliance, business operations, and product teams to deliver secure and scalable solutions.
Demonstrated ability to translate ambiguous business needs into practical MVPs, execution plans, team priorities, measurable outcomes, and adoption plans.
Ability to communicate clearly with senior stakeholders while staying close to execution details, risks, dependencies, and delivery health.
Bachelor’s degree in computer science, Data Science, Artificial Intelligence, Engineering, Information Systems, Business Technology, or a related field; advanced degree or relevant cloud, AI, automation, data, quality, or security certifications preferred.
Demonstrated ownership of a portfolio of applications and solutions, including accountability for their roadmap, stability, lifecycle management, and continuous improvement.

Responsibilities

Lead AI engineering teams that design, build, and scale AI-enabled business solutions across investment systems.
Translate target operating model priorities into delivery plans, team backlogs, MVP scopes, operating rhythms, and measurable outcomes.
Partner with business and technology stakeholders to identify workflow pain points, automation candidates, agent insertion opportunities, and data dependencies.
Deliver smart automation and human-plus-agent patterns that improve cycle time, straight-through processing, exception handling, resiliency, and user experience.
Guide engineering teams on practical use of generative AI, agentic AI, orchestration, retrieval-augmented generation, evaluations, observability, guardrails, and reusable delivery patterns.
Embed responsible AI practices, human-in-the-loop controls, auditability, traceability, secure access, data controls, and operational guardrails into delivery from the start.
Develop managers, senior engineers, workflow analysts, automation specialists, and domain-savvy technologists while strengthening a one-team culture across Charlotte and global hubs.
Communicate progress, risks, dependencies, and business value clearly to the AI Engineering Director, peer leaders, product partners, and senior stakeholders.