Project Manager (Application Documentation & Knowledge Base Program)

About the role

We are looking for an experienced Project Manager to lead a multi‑application documentation and knowledge‑base program. The role coordinates engineering, SMEs, QA, and business stakeholders to ensure consistent scope control, deliverable tracking, and governance of AI usage and data security across each new application engagement.

Key responsibilities

• Own the end‑to‑end project plan for each application, covering gap assessment, code analysis, data‑flow documentation, architecture mapping, business process mapping, knowledge‑base build‑out, and testing/QA readiness.
• Develop and maintain a repeatable playbook to scope and kick‑off new application engagements efficiently.
• Track and manage all deliverables (gap assessments, architecture docs, API/database inventories, workflow maps, knowledge‑base entries, final readouts) across multiple concurrent or sequential applications.
• Coordinate engineering staff, technical writers, application SMEs, QA, and business stakeholders for each scoped application.
• Schedule and run knowledge‑transfer sessions, status calls, and final readout presentations.
• Manage risks such as documentation gaps, SME dependency, high‑technical‑debt zones, and ensure AI usage stays within security/compliance boundaries.
• Maintain traceability logs linking documentation to code, databases, APIs, and business workflows.
• Oversee version‑control processes for documentation updates and escalate scope changes or blockers.

Required profile

• 5+ years of project‑management experience, preferably in software documentation, modernization, or discovery engagements.
• Experience managing vendor/client relationships in enterprise or regulated environments.
• Familiarity with legacy application ecosystems across varied tech stacks.
• Strong deliverable‑tracking and reporting discipline across multiple workstreams.
• PMP or similar certification is a plus.
• Excellent stakeholder communication and presentation skills.

Required skills

• AI usage compliance and data‑security awareness.
• Documentation and version‑control best practices.