Technical Program Manager

Core Expectations AI & Agentic AI in program management Build agentic workflows: stand up AI agents wired into Jira, Slack and BI to collect status, chase updates and maintain tracker hygiene. Agentic reporting: move updates, exec summaries and review decks from manual assembly to agent-generated drafts you review and sharpen. Risk prediction: use AI on velocity, ageing, blocker and dependency signals to flag at-risk milestones before they slip. Planning support: apply AI to backlog grooming, requirement gaps, estimation sanity-checks and dependency mapping. Human-in-the-loop governance: define where agents act autonomously vs. need review; own accuracy and auditability of AI outputs. Drive adoption: pilot agent frameworks and MCP/API integrations, scale what works across the PMO, and track hours saved. Roadmap end to end Own the full cycle: intake priority conclusion capacity planning cutline concluded, published roadmap. Priority conclusion: drive structured prioritisation with Product, Engineering and Business to a documented decision. Capacity planning: build a realistic capacity view by team and skill - leaves, hiring ramp, KTLO/BAU load, buffer. Cutline: match demand to capacity, draw a defensible line, and communicate what's committed vs. deferred. Conclude & hold: lock and publish the roadmap with owners, milestones and dependencies; manage change control against it. Planning & delivery end to end Own delivery with full accountability for timeline, scope and quality - from scoping to release. Build bottom-up execution plans: work breakdown, estimates, sequencing, critical path, dependencies. Own milestone gates (PRD signoff, Tech design, Dev Done, QA Signoff, Release), sprint rigour and backlog readiness. Mitigate risks, dependencies and bottlenecks early, and escalate decisively. Stakeholder management: align Product, Engineering, QA, Design, Business and leadership; drive decisions without direct authority. Executive dashboards & reporting: own dashboards (Jira/Sheets/BI) and prepare leadership decks with insights, risks and asks - not raw status. Improve delivery KPIs (Say-Do ratio, velocity, cycle time, release predictability) and run the delivery cadence. What We're Looking For 3–8 years in Program Management / Delivery Management / TPM roles in product or tech-driven teams. Hands-on roadmap ownership (must-have): you have personally run prioritisation, capacity planning, cutline calls and roadmap conclusion. Proven end-to-end planning: owned deliverables from scoping to release and been accountable for the dates. Real, hands-on use of AI: concrete examples of workflows you have automated; agentic AI exposure is a strong plus. Strong grasp of Agile/Scrum and the product development lifecycle; hands-on with Jira, dashboards and delivery metrics. Strong stakeholder management and executive communication: able to influence senior stakeholders and present reports that land with leadership. Basic technical understanding: comfortable with technology fundamentals and the startup ecosystem; can follow architecture, API and release discussions. Strong analytical and problem-solving skills; comfortable driving clarity in ambiguity. Good to Have Quarterly/annual planning for a multi-pod engineering org, or a PMO built from scratch. Low-code automation (Apps Script, Jira automation, n8n) and prior high-growth startup experience.