Staff Product Manager, Agentic Experiences

Clari + Salesloft

3d•$129,000 - $190,000•Remote

About The Position

Clari + Salesloft are building the next era of enterprise revenue — one where teams make confident decisions powered by AI and real signals. By combining our scale, insights, and AI innovation, we’re building the industry’s first Predictive Revenue System, enabling humans and AI to work together to make smarter decisions and drive consistent growth. With thousands of customers using our platforms every day, we have an unmatched view into how revenue is actually won — the Revenue Context that reveals what happens, when, and with what outcome. This gives us a unique opportunity to transform an entire category and set a new benchmark for how modern revenue teams operate. Join us to help transform how companies around the world run revenue — and build the platform that will guide leading revenue teams into the future. At Clari + Salesloft, our Staff Product Manager, Agentic Experiences will be pivotal to our company’s success. You will be a key member of our fast-growing and high-performing product management team, owning the agentic experiences that define how AI works alongside sellers. We believe the best products come from small, empowered pods of product, design, engineering, and data science in tight collaboration. On a day-to-day basis, you will be responsible for setting the product direction for how AI agents act on a seller's behalf, turning an ambiguous, fast-moving problem space into a clear strategy and a shipping roadmap.

Requirements

8+ years of product management experience in a B2B SaaS environment. Ideally in sales technology, revenue intelligence, or an adjacent vertical.
Deep understanding of how enterprise sales teams operate: deal structure, multi-stakeholder dynamics, buying committee complexity, and how revenue leaders coach and manage performance.
Demonstrated experience building or shipping AI/ML-powered product features. You know how to evaluate model capabilities critically, communicate tradeoffs clearly, and design experiences that make AI trustworthy and actionable.
Experience with agentic AI systems, next-best-action frameworks, or intelligent workflow automation, either as a product builder or as a sophisticated buyer/user.
Strong platform intuition: you've owned or contributed to API strategy, developer experience, or enterprise admin capabilities before.
Experience with CRM integrations and an understanding of data sync complexity, bidirectional workflows, and the trust challenges that come with maintaining data fidelity across systems.
Track record of shipping multi-channel communication products or workflow orchestration at scale, with strong opinions on what makes execution experiences actually useful to sellers.
Exceptional ability to hold both strategic vision and ground-level execution detail simultaneously. You write sharp strategy docs and also obsess over edge cases in user flows.
Strong communicator who can adapt their message for engineers, designers, executives, and customers.

Nice To Haves

Experience with signal-based or intent-driven product capabilities (first-party behavioral data, third-party data enrichment, or event-driven architectures) is a meaningful plus.

Responsibilities

Own the end-to-end product strategy for our agentic selling experiences. This is a complex, fast-moving problem area where you’ll set direction, sequence the roadmap, and resolve hard tradeoffs with limited precedent.
Define what it means for AI agents to act on a seller’s behalf by designing agentic experiences that are transparent, controllable, and trustworthy, with the right guardrails, human-in-the-loop checkpoints, and evaluation criteria for agent quality.
Exercise deep product judgment on novel problems by selecting the methods, frameworks, and success metrics for work that doesn’t yet have an established playbook, and pressure-testing your approach through peer and cross-functional review.
Lead through influence as a cross functional leader and coordinating cross-functional pods across engineering, design, and data science, and guiding and mentoring other product managers without direct reporting authority.