Project Manager Jobs

About The Position

Requirements

• 3+ years in technical program, delivery, or project management for software teams.
• Technical enough to read code, follow architecture discussions, and debug process problems at the root.
• Hands-on with both Scrum and Kanban (hybrid ideal)
• Fluent in an issue tracker like Linear or Jira
• Strong written communication — we're async-first, and writing is how work gets specified and reported.
• You use AI daily to write, analyze, and accelerate your work.

Nice To Haves

• Scrum Master certification (or equivalent experience) strongly desired — evidence of having led Agile teams with a deep command of the process, not just having been part of one.
• Startup ambiguity tolerance
• Customer-facing comfort
• Workforce management / scheduling / HR-tech domain experience
• Experience coordinating AI-assisted or agent-driven development

Responsibilities

• Own the agile process, end-to-end — a hybrid of Sprint/Scrum for committed work and continuous Kanban for interrupts, bugs, and maintenance. Run planning, standups, retros, and refinement efficiently, protect maker time, drive commitments to completion, and keep tuning the process as the team grows.
• Manage prioritization and roadmap alignment — keep engineering execution aligned with product priorities in Linear, from requirements through initiatives, projects, and shippable features (with Definition of Ready / Done discipline), and give leadership grounded feedback on what's realistically achievable.
• Facilitate stakeholder alignment — work across Product, Operations/Customer Success, and Go-to-Market to surface customer and business needs into priorities, and manage timeline and trade-off expectations in the other direction.
• Oversee reporting, dependencies, and risk — keep leadership informed with clear weekly status and delivery metrics (velocity, cycle time, throughput); track cross-team and cross-repo dependencies in a living RAID-style picture, and escalate before risks become slips.
• Manage cross-pod coordination and onboarding — keep our engineering pods aligned, unblocked, and shipping, run new-customer rollouts as projects across data integrations, backend, and frontend, and work hands-on with our AI agents — where your crisp write-ups and acceptance criteria become engineering throughput directly.