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United States
Onsite
With over 30,000 customers, including a third of Fortune 500 companies, Tempo is trusted by organizations across the globe to make their workflows work better.
We create a suite of integrated solutions for time management, resource planning, budget management, roadmapping, program management, reporting and more. We create the tech that enables the modern team to deliver – for every step from first vision to value.
Since our beginning in 2007 as a project to make a time-tracking tool to help a client – Tempo has expanded to become the #1 time management add-on for Jira, and we have developed and acquired a multitude of tools to become one of the most trusted names in the Atlassian ecosystem.
We want everyone to work better – but we also want to be a tech company with a heart. Join us as we continuously innovate our award-winning products, create new solutions, and help the world work smarter, not harder.
About the role:
Most enterprise software gives users data. Loop gives users decisions. The Recommendations Skill is the engine behind that distinction — and it is the hardest product problem in the platform to get right.
We are looking for a Product Manager who has operated at the intersection of AI systems, enterprise planning, and organizational decision-making. You may have come from management consulting, decision intelligence, enterprise architecture, or a data product role where you were responsible not just for surfacing information but for making that information actionable at scale. You understand that an AI recommendation is only as good as the trust the organization places in it — and that trust is built through transparency, governance, and the ability to explain why a recommendation was made.
This group owns the full recommendation lifecycle: signal ingestion and synthesis, insight generation, rule-based evaluation, recommendation creation, governance and approval workflows, and the batch re-evaluation engine that keeps the plan current as conditions change. It is a systems-level product challenge with a direct line to customer outcomes.
What you’ll do:
The end-to-end product strategy and roadmap for Loop's Recommendations Skill — from signal to approved action
Planning rules as a first-class product concept: how organizations define, manage, and version the guardrails that govern when and how recommendations are generated
The recommendation surface: how Loop presents prioritized, explainable recommendations to the right stakeholder at the right moment — with full reasoning visible
Governance and approval workflows: how recommendations move through human review, queuing, escalation, and batch approval without creating bottlenecks or losing context
Batch re-evaluation: how Loop continuously re-scores open recommendations as new signals arrive, ensuring the plan reflects current reality — not last quarter's assumptions
Competitive analysis integration: how external market signals and competitor movements are weighted into portfolio recommendations
Discovery with Chief Strategy Officers, portfolio leaders, PMO heads, and enterprise architects who are responsible for keeping large organizations strategically aligned
The recommendation engine you will be building around
Loop's Recommendations Skill is not a notification system or a dashboard with suggested actions. It is a continuous, AI-led planning layer that operates on the following model — which you will own, challenge, and evolve:
Signals — the raw inputs: portfolio KPIs, delivery metrics, capacity utilization, demand forecasts, market data, competitive intelligence feeds, and internal stakeholder inputs. Signals are always on; the system is always listening.
Insights — synthesized patterns derived from signals. An insight is not a data point; it is a conclusion. 'Three high-priority initiatives are competing for the same critical skill pool in Q3' is an insight. The system generates insights continuously and ranks them by strategic relevance.
Planning Rules — the organization's encoded decision logic: investment thresholds, risk tolerances, strategic priorities, compliance constraints, and governance policies. Rules determine which insights escalate into recommendations and shape how those recommendations are framed.
Competitive Analysis — external signals from market intelligence feeds and competitor monitoring that contextualize internal portfolio decisions. A capacity reallocation recommendation looks different when a competitor has just announced a product in the same space.
Demand Management — the interface between incoming work requests and available portfolio capacity. Loop evaluates new demand against current commitments and generates intake recommendations that reflect real constraint, not optimistic capacity math.
Recommendations — prioritized, explainable actions surfaced to the right stakeholder. Every recommendation carries its full reasoning chain: which signals triggered it, which planning rules evaluated it, what the expected outcome of acting vs. not acting is.
Governance & Approval — the organizational layer. Recommendations enter a structured queue where they are routed by type, urgency, and authority level. Approvers see full context. Batch approval enables high-volume processing without sacrificing accountability. Escalation paths handle exceptions.
Batch Re-evaluation — the continuous intelligence layer. As new signals arrive, open recommendations are automatically re-scored. A recommendation that was urgent last week may be superseded; a deferred one may become critical. The plan stays live.
Who you are:
3-5 years in a role where you were responsible for making AI, data, or ML systems actionable inside complex organizations — consulting, decision intelligence, enterprise product management, or strategic advisory
Deep familiarity with how enterprise planning decisions actually get made: who has authority, how recommendations move through governance, and why good analysis so often stalls at the approval stage
Experience with AI recommendation systems, rules engines, or decision automation — either as a builder, a buyer, or an implementer who has seen them fail and understands why
Genuine sophistication about what makes an AI recommendation trustworthy: explainability, auditability, calibration, and the organizational conditions under which humans will act on machine-generated guidance
Fluency with the concepts that feed this system: demand management, competitive intelligence, portfolio governance, scenario planning, and risk-adjusted prioritization
Comfort working directly with AI tools to accelerate your own work — you are already using LLMs to think through product problems, draft requirements, and stress-test logic. This is expected and foundational here.
Ability to hold systems complexity without losing sight of the user: the person on the receiving end of a recommendation is a busy executive who needs to trust it in thirty seconds
Strong written communication; you can write a crisp one-pager that earns alignment without a meeting
Why Join Tempo?
Impact: Work on meaningful products that empower enterprise users and improve productivity.
Innovation: Be part of a culture that values creativity and innovation, with opportunities to make a real impact.
Collaboration: Join a supportive, collaborative UX team that values openness, communication, and a continuous learning environment.
Growth: Opportunities for professional development, including conferences, courses, and mentorship.
What's In It For You (Org-wide) -
Remote First work environment
Unlimited vacation in most of our locations!!
Great benefits including health, dental, vision and savings plan.
Perks such as training reimbursement, WFH reimbursement, and more.
Diverse and dynamic teams with challenging and exciting work.
An opportunity to have a real impact on our business.
A great range of social activities (both in person and virtual).
Optional in person meet-ups and the ability to travel to our international offices
Employee referral program
And so much more!
Note: As our hiring teams are global, please submit your resume in English only
Apply today to join the Tempo team and help shape the future of enterprise productivity software.
Join us at Tempo Software, where we proudly foster an equal opportunity workplace. We are committed to creating an inclusive culture where all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.