Agentic Engineering Manager

Manager role focused on leading AI agent teams, orchestrating work intake, stakeholder management, quality oversight, and setting guardrails for agent-driven delivery within a consulting firm's Government & Public Services practice.

What you'd actually do

  1. Orchestrate work intake, prioritization, and assignment across the value stream
  2. Lead stakeholder management, translating business needs into clear acceptance criteria for agent teams
  3. Provide quality oversight and completeness verification—ensuring "done" truly means done
  4. Set guardrails, define constraints, and establish risk controls for agent-driven delivery
  5. Coordinate dependencies across teams and manage delivery rhythm (planning, reviews, escalations)

Skills

Required

  • Bachelor's degree in Computer Science, Data Science or Engineering
  • 5+ years of experience in delivery leadership, product management, or program management roles
  • 5+ years of experience defining acceptance criteria, quality standards, and release readiness gates
  • 5+ years of Agile & Lean practices experience, including sprint planning, backlog refinement, retrospectives, continuous improvement
  • 2+ years of experience with AI-assisted development tools and their capabilities/limitations
  • Ability to travel 50%, on average
  • Must be legally authorized to work in the United States without the need for employer sponsorship
  • Must be able to obtain and maintain the required clearance for this role

Nice to have

  • Stakeholder management skills with ability to balance competing priorities
  • Strong facilitation and communication skills for planning sessions, reviews, and escalations
  • Track record of improving delivery flow, reducing bottlenecks, or optimizing team processes

What the JD emphasized

  • agent teams
  • agent-driven delivery
  • agent workflows

Other signals

  • Orchestrate work intake, prioritization, and assignment across the value stream
  • Lead stakeholder management, translating business needs into clear acceptance criteria for agent teams
  • Provide quality oversight and completeness verification—ensuring "done" truly means done
  • Set guardrails, define constraints, and establish risk controls for agent-driven delivery
  • Coordinate dependencies across teams and manage delivery rhythm (planning, reviews, escalations)