AI-Augmented Technical Project Manager
Most project management roles ask you to track what engineers decide. This one asks you to understand what they're building well enough to plan it accurately — and to use AI tooling to do that faster than a traditional PM could.
You will coordinate engineering, QA, product, and business teams across concurrent workstreams. That means interpreting system architecture and application flows, not just managing a JIRA board. It means catching dependencies before they become blockers, and translating technical complexity into timelines that stakeholders can act on.
The AI-native expectation here is concrete, not aspirational. You are expected to use tools like ChatGPT, Copilot, and Claude to draft status reports, generate meeting summaries, and build risk logs faster. You will apply AI-assisted automations to JIRA and Excel for dashboards and velocity tracking. And you will factor in how AI-assisted coding and testing are compressing engineering timelines — because a sprint plan that ignores that is already out of date.
Who thrives here
You have six to eight years in technical project or program delivery, and you are comfortable enough with Java-based environments and system architecture to have a real conversation with engineers. You follow through without being chased. You surface risk early, not after it lands. You see AI tooling as a working habit, not a talking point.
What you'll own
- Own end-to-end project planning, execution, tracking, and delivery across multiple concurrent workstreams
- Drive sprint planning, task prioritisation, and status reporting in JIRA
- Prepare and maintain trackers, dashboards, reports, and execution plans in Microsoft Excel
- Identify delivery risks, blockers, and dependencies proactively and drive their resolution
- Facilitate stand-ups, sprint reviews, retrospectives, and governance calls
- Align internal and external stakeholders on scope, timelines, milestones, and deliverables
- Interpret system architecture and application flows; translate technical challenges into realistic plans
- Monitor project health, velocity, and milestones; support release and deployment coordination
- Apply AI tools to accelerate reporting, risk logging, dashboard generation, and velocity tracking
What it takes
- 6–8 years in technical project, program, or delivery management
- Strong grasp of PM methodologies including Agile and Scrum
- Hands-on JIRA experience and strong working knowledge of Microsoft Excel
- Good understanding of Java and Java-based application development environments
- Good understanding of system architecture, components, workflows, APIs, and technical dependencies
- Strong communication, stakeholder management, and follow-up skills
- Fluency in using AI tools (ChatGPT, Copilot, Claude) for delivery tasks such as status reports, meeting summaries, and risk logs
- Understanding of how AI-assisted coding and testing affect engineering delivery timelines
Nice to have
- Ability to manage multiple competing priorities across parallel workstreams
We respond to every application within 2 business days.