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 solid 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.

📌 Technical Program Manager (Haryana)
🏢 Spinny
📍 Haryana