Product Management Lead, AI at AECOM

USA
April 2, 2026
Full Time Remote
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Job Description

The Product Management Lead, AI is responsible for driving product strategy, delivery, and value realization for AI-powered solutions integrated into enterprise operations. This leadership role focuses on ensuring AI products are effectively adopted, trusted, and aligned with business goals while maintaining responsible AI standards.

Location: Orlando, FL (Remote Eligible)
Employment Type: Full-time
Salary: USD 170,000 – USD 220,000 yearly

Key Responsibilities

  • Lead the roadmap and strategy for AI and agentic product portfolios, defining where AI should assist, advise, or act autonomously
  • Translate business needs and process insights into AI-ready product backlogs, including workflows, guardrails, and success metrics
  • Drive product decision-making by balancing value vs. risk, autonomy vs. control, and cost vs. quality
  • Define evaluation criteria, trust thresholds, and performance metrics for AI solutions
  • Collaborate with architecture, data, and engineering teams to align AI solutions with business objectives
  • Oversee adoption strategies, ensuring AI products are effectively integrated and deliver measurable impact
  • Establish governance frameworks with Responsible AI, Legal, Risk, and Operations teams
  • Mentor and lead Product Managers, strengthening AI product development capabilities

Requirements

  • Bachelor’s degree with at least 12 years of product management experience, including AI-enabled solutions
  • Minimum of 4 years in a product leadership role
  • Proven track record managing AI product outcomes, including adoption and business impact
  • Experience translating business problems into AI-driven product strategies and workflows
  • Strong understanding of AI risk, trust, and cost considerations
  • Previous experience in a Solution Architect or similar role is an advantage
  • Excellent stakeholder management and communication skills

Preferred Qualifications

  • Experience defining autonomy levels and human-in-the-loop (HITL) systems
  • Familiarity with agentic workflows, RAG systems, and AI evaluation frameworks
  • Knowledge of AI performance metrics such as accuracy, explainability, and bias control
  • Experience working in regulated or high-risk environments
  • Ability to collaborate with technical teams without owning implementation

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