Lead Technical Program Manager

Role Summary

This mid-level Agility Lead / Scrum Master / Project Manager owns delivery outcomes by flexing between agile facilitation and project management execution as the work necessitates. The role drives predictable delivery through proactive ownership, disciplined follow-through, and clear, timely communication across stakeholders, teams, and vendors as applicable.

Delivery may include agile, plan-driven, or hybrid approaches, and this role adapts the cadence, artifacts, and governance to fit the context while maintaining transparency, accountability, and delivery control. The role is also expected to explore and practically leverage approved AI-enabled tools to improve efficiency (for example, notes/summaries and reporting insights) within firm policies, confidentiality constraints, and ethical use expectations.

Job responsibilities

  • Proactively facilitate agile ceremonies as needed—standups, backlog refinement, sprint planning, reviews, and retrospectives.
  • Drive hands-on JIRA support and administration, keeping backlog and data clean for effective planning, tracking, and reporting.
  • Lead end-to-end project management, actively coordinating planning, governance, and delivery across teams and workstreams.
  • Build and manage integrated schedules using PM tools, tracking milestones, dependencies, and critical paths.
  • Own scope, timelines, and milestones; lead trade-off discussions and flag changes early with clear options and impacts.
  • Maintain and drive RAID logs and delivery controls, ensuring clear ownership, due dates, and disciplined closure.
  • Draft and synthesize notes, extract actions and decisions, and create stakeholder-ready summaries.
  • Provide PM operations and admin support—intake, triage, roadmap updates, Confluence content, meeting coordination, agendas, notes, action logs, and delivery artifacts.
  • Proactively leverage approved AI tools to boost efficiency and quality.

Required qualifications, capabilities, and skills

  • 3+ years of experience as a Scrum Master and/or Project Manager supporting technology delivery in agile, plan-driven, or hybrid environments.
  • Demonstrated ability to flex between Scrum Master facilitation and core PM responsibilities based on delivery needs.
  • Strong written and verbal communication skills, including effective horizontal and vertical communication, with consistent stakeholder follow-up and proactive closure of open items.
  • Strong foundational skills/Practical hands on experience with JIRA, Confluence and Excel, tracking, dependency management, and delivery reporting.
  • Proven track record of proactive ownership, strong follow-through, and reliable execution under shifting priorities.

Preferred Qualifications, capabilities and Skills

  • Experience in regulated, high-control, or governance-heavy environments, including hybrid delivery models.
  • Certifications a plus, not required (for example, CSM or PSM, SAFe Scrum Master, PMP, or equivalent).
  • Hands-on experience with Microsoft Copilot and/or similar AI assistants is a major plus, including willingness and ability to leverage AI responsibly to improve efficiency within enterprise policy constraints.
  • Experience with Teams, Microsoft Project a plus

Key Competencies and Behaviors

  • Proactive, ownership-driven execution with a strong bias for action and close-the-loop follow-through.
  • Strong facilitation skills and the ability to influence without authority across teams and stakeholders.
  • Planning discipline, including comfort with milestones, integrated schedules, dependencies, and delivery controls.
  • Stakeholder management and governance rigor, including concise status reporting and decision/approval management.
  • Risk and issue management mindset with early surfacing, practical mitigation options, and clear escalation.
  • High attention to detail for operational hygiene (actions, decisions, RAID, and JIRA data quality) without losing sight of delivery outcomes.
  • Practical experimentation mindset with responsible use of approved AI tools, including validation of outputs and strict adherence to confidentiality and policy expectations.

See also

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