Full Time
1200
40
Mar 20, 2026
NO TO CORPORATE/DEMOCRATIC type of person, we want someone who has experience with startups. Less words, more actions and deliverables
We’re hiring a full-time Technical Project Manager to bring structure, clarity, and delivery discipline to fast-moving work across AI, automation, and software delivery.
I’m not afraid to get hands-on with clients — what I need is someone who can turn everything I’m planning into a well-structured, clearly prioritised execution system inside Linear, and keep delivery consistent.
Schedule
Full-time
- 9:00 AM – 5:00 PM CST (required availability)
What you’ll do
- Own execution structure in Linear: epics, issues, milestones, dependencies, priorities, and sprint planning.
- Translate ideas, client needs, and technical direction into clear tickets with acceptance criteria and next steps.
- Run Agile delivery: backlog grooming, sprint planning, standups, retros, and delivery tracking.
- Coordinate with technical tea
- Maintain project documentation: SOPs, technical notes, decision logs, and process documentation.
- Keep stakeholders aligned: proactive updates, risk tracking, blocker removal, and scope control.
- Improve speed and consistency through better systems, tooling, and automation where relevant.
Requirements (must-have)
- Proven experience in Technical Project Management (software/IT delivery).
- Strong understanding of Agile (Scrum/Kanban), including planning, estimation, and sprint execution.
- GitHub-native with a solid understanding of Git flow (branches, PRs, reviews, releases).
- Experience maintaining strong documentation and keeping projects “auditable.”
- Excellent written communication and confidence working with clients/stakeholders.
- Strong organisation and the ability to manage multiple moving parts without dropping details.
Major plus
- Experience accelerating delivery with AI and automation (workflows, tooling, prompt systems, process automation).
Bonus +++
- Familiarity with the Anthropic (Claude) ecosystem
- Understanding of MCPs (Model Context Protocol) and tool-enabled workflows
- Ability to use AI tools securely and responsibly (data handling, permissions, safe execution)
Tools
- Linear, GitHub, Slack, Notion/Docs
- Automation tools (Zapier / Make / n8n or similar)