This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Product Manager, WFI based in the United States.
As Senior Product Manager, Workforce Intelligence, you will lead an emerging enterprise product from early market validation into a durable, scalable business. You will own the product strategy, roadmap, and commercial outcomes, with success measured through adoption, retention, and revenue. Working closely with engineering and design, you will turn complex customer problems into clear hypotheses, experiments, and product decisions. You will engage directly with senior engineering leaders to understand how organizations measure AI productivity, spend, risk, and value. The role combines product discovery, technical fluency, data-driven experimentation, and cross-functional leadership across sales, marketing, customer success, finance, and product. You will also help define new approaches to AI attribution, benchmarking, reporting, and agent governance in a rapidly evolving category.
Accountabilities:
- Own the Workforce Intelligence product strategy and roadmap, connecting priorities to activation, adoption, retention, and revenue outcomes.
- Conduct continuous discovery with CTOs, VPs of Engineering, engineering managers, and design partners to understand how enterprises evaluate AI tools, productivity, spend, and risk.
- Translate uncertain customer problems into testable hypotheses, rapidly prototype solutions, run experiments using real customer data, and discontinue initiatives that do not demonstrate sufficient value.
- Lead the evolution of trusted AI attribution and reporting, connecting activity and cost at the work-item level to executive insights around throughput, delivery timelines, capacity, and savings.
- Develop the product vision for agent oversight, including identifying agent-only work, connecting it to funded initiatives, explaining associated costs, and providing appropriate context for reviewing results.
- Shape benchmarking approaches for AI tools and models using customers' own teams and workflows, with transparent methodologies and clearly communicated confidence levels.
- Define connector and data strategies spanning AI providers, developer environments, source control, work management, collaboration tools, and related products.
- Collaborate with product leaders across timesheets, capacity planning, financial management, and other product areas to create connected customer value while maintaining clear ownership and sequencing.
- Partner with sales, marketing, and customer success on positioning, pricing, packaging, launches, enablement, adoption, and expansion.
- Establish instrumentation, product metrics, and operating rhythms that support evidence-based decisions and visible trade-offs across customer value, technical feasibility, trust, and commercial impact.
- Represent Workforce Intelligence with customers, partners, platform stakeholders, and senior leaders, communicating a clear product perspective and building alignment across competing priorities.
- Work directly with engineering and design from problem definition through delivery in a small, dedicated team with high ownership and minimal handoffs.
- Use AI collaboratively in day-to-day product work to improve communication, experimentation, and delivery efficiency.
Requirements:
- 5+ years of product management experience, including end-to-end ownership of a B2B SaaS or data product serving technical audiences.
- Demonstrated success improving adoption, retention, expansion, or revenue, with the ability to clearly explain the decisions, metrics, and outcomes behind your work.
- Experience taking a product or significant product area from discovery through launch and growth while partnering closely with engineering, design, and go-to-market teams.
- Strong product judgment in ambiguous or emerging markets, with the ability to distinguish interesting capabilities from meaningful customer problems and build clear investment cases.
- Deep customer discovery experience across interviews, usage data, prototypes, and live product experiments.
- Experience designing experiments capable of disproving product hypotheses rather than simply validating existing assumptions.
- Comfort working with imperfect, incomplete, or inferred data, clearly communicating confidence levels and limitations.
- A track record of changing product direction when customer evidence contradicts the original plan.
- Experience with developer tools, engineering intelligence, data and analytics products, AI governance, or another technically complex enterprise product.
- Working knowledge of software delivery workflows, including Jira work items, source control, pull requests, engineering performance measures, and the role of AI tools and agents in modern development.
- Strong data fluency and the ability to collaborate with engineering and analytics teams on attribution models, instrumentation, benchmarks, and reporting methodologies.
- Experience with the Atlassian ecosystem or another platform and marketplace business is an advantage.
- Hands-on experience with modern AI tools and a thoughtful perspective on where AI can generate measurable value versus unreliable or misleading outputs.
- Understanding of AI product considerations including model evaluation, agent behavior, privacy, governance, cost, and rapidly evolving vendor capabilities.
- Ability to establish trustworthy measures of human and AI-assisted work and clearly distinguish supported conclusions from areas of uncertainty.
- Strong communication and presentation skills, with the ability to explain complex technical and commercial concepts without relying on unnecessary jargon.
- Demonstrated ability to align engineering, design, sales, marketing, customer success, finance, and executive stakeholders around shared outcomes without relying on direct authority.
- Credibility with senior technical buyers and a strong curiosity about how they make product, technology, and investment decisions.
- Low attachment to individual ideas and a strong commitment to evidence, outcomes, and continuous learning.
Benefits:
- Remote-first work environment.
- Unlimited vacation in most locations.
- Health, dental, and vision coverage, along with a savings plan.
- Training reimbursement and work-from-home reimbursement.
- Professional development opportunities, including conferences, courses, and mentorship.
- Diverse and dynamic teams working on challenging and meaningful projects.
- Opportunities to make a direct impact on the business and enterprise productivity.
- Social activities, including virtual and in-person events.
- Optional in-person meetups and opportunities to travel to international offices.
- Employee referral program.
- Applications should be submitted with a resume in English.
- Equal opportunity workplace committed to an inclusive culture and consideration of qualified applicants without regard to protected characteristics.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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