Agentic AI Engineering Manager

Role overview

Technical leadership

• Build and maintain shared repositories, CI/CD pipelines, evaluation tooling, and data access standards.
• Protect code quality, security, and maintainability, and turn agent-generated prototypes into production-quality features.
• Direct AI coding-agent workflows, review outputs, and maintain prompt libraries and evaluation datasets.
• Coordinate with central Data/Analytics, Security, and legal/compliance teams.

People and pod management

• Own hiring, onboarding, mentoring, performance management, career planning, and time-off approvals.
• Drive agentic AI tooling adoption, evaluate success metrics, and improve engineering practices.
• Plan and prioritize the pod backlog, capacity, throughput, and delivery quality.
• Oversee cybersecurity, governance compliance, and commercial software license renewals.
• Coach engineers and align delivery with business risk, budget, and cost constraints.

Essential skills and experience

• Seven or more years architecting enterprise solutions and specializing in complex business systems and workflows.
• Proficiency in construction project management software and lifecycle information management for BIM, such as ISO 19650.
• Experience managing an AI PDLC process and directing agentic tools through planning, development, and delivery.
• People-management and technical-leadership experience in fast-paced agile environments.
• Ability to combine hands-on coding or code review with people-management responsibilities.
• Strong business acumen and proficiency in object-oriented programming.
• Apply ethical AI principles including privacy, explainability, transparency, and bias mitigation.