Product Manager (B2B, SaaS product)

About the Role
We’re looking for an AI-Forward Product Manager to help shape the next generation of Revenue Grid’s Revenue Intelligence platform.
This is a high-impact role for someone who wants to work at the intersection of B2B SaaS, SalesTech, AI, and enterprise workflows. You’ll help move the platform beyond static outbound sequencing and rigid cadences toward agentic workflows, generative personalization, real-time intent signals, and AI-driven coaching and deal guidance.
The remit covers Revenue Grid’s full Intelligence pillar: Engagement, Coaching, Signals, Account Intelligence, and Call Intelligence.
Across each of these areas, the mission is the same: evolve rules-based logic and manual review into model-driven judgment and own the strategy and execution behind it. You’ll build capabilities that augment or automate the daily work of B2B sellers and the managers who coach them.
This role offers significant product ownership, close collaboration with cross-functional teams, and the opportunity to directly influence how AI becomes part of real enterprise sales workflows.

What You’ll Do
Own the Autonomous Roadmap: Define and ship AI-native features such as automated account/buyer research, dynamic email composition, and context-aware deal-risk recommendations.
Own Call Intelligence, AI-Native: Replace keyword spotting and static rubrics with LLM-driven conversation understanding; talk-track adherence, competitive mentions, sentiment, and objection handling, across call sources including Zoom, GoToMeeting, and native dialers.
Own AI Coaching: Turn call and meeting evaluation into coaching reps actually act on: skill-gap detection, rep-specific improvement plans, and manager-facing team trends, generated by the model instead of a static scorecard.
Own Signals & Deal Guidance: Build the layer that turns relationship and communication patterns into prioritized, explainable risk and opportunity signals, plus next-best actions surfaced directly in seller and manager workflows.
Establish AI Trust, Evals & Governance: Build testing metrics that catch model hallucination, judge output quality, and monitor latency against real seller and coaching behavior. Define how autonomous agents act independently while staying transparent, controllable, and explainable, in line with responsible-AI, privacy, and compliance requirements.
Bridge the Data-to-Workflow Gap: Make sure AI insights from Coaching, Signals, and Call Intelligence translate natively into CRM infrastructure (Salesforce, HubSpot) and execution layers without breaking data fidelity.
Cross-Functional AI Leadership: Lead a pod of LLM engineers, UX designers, and product marketers to validate prototypes quickly before building, and mentor fellow PMs on AI-native practice even without formal authority over their teams.
Shape AI Packaging & Monetization: Partner with Finance and GTM leadership on how AI-native capabilities are packaged, priced, and positioned as they move from beta to GA.
Represent AI Strategy Externally: Engage customers, prospects, and industry analysts on Revenue Grid’s AI roadmap and positioning.
Work with customers, partners, and prospects to effectively capture requirements and opportunities, ensuring smooth communication and requirement transition from the client to the internal team and vice versa.
Be Customer-Centric & Hypothesis-Driven: Work with customers, partners, and prospects to ground the roadmap in customer reality, not assumption: form a hypothesis, ship the smallest testable version, and let feature-usage metrics tell you what to build next.

What We’re Looking For
5+ Years in B2B SaaS PM: Proven track record in Revenue Operations, Sales Engagement, or conversational intelligence.
Deep Revenue Engagement Domain Expertise: You have either built features inside these tech stacks or are a sophisticated enterprise power-user/admin who understands how reps use cadences, triggers, and snippets.
Conversation & Coaching Intelligence Background: Experience with call-recording, conversation-intelligence, or coaching/enablement products (Gong, Chorus, Clari, or similar), including where keyword-spotting and rules-based scoring break down and what changes rep behavior.
Shipped AI in Production: You have designed, deployed, and scaled at least one major model-powered or LLM-driven feature, with a probabilistic mindset for designing graceful failures when an AI output is flawed.
API & Integration Intuition: Strong data fluency. You know how data moves across GTM tools and where sync tends to break.
Platform & Enterprise Admin Fluency: Comfortable defining API strategy, business workflow analysis, process analytics and enterprise-grade administration/configuration for a multi-tenant SaaS platform, not just individual features.
Responsible AI Exposure: Working familiarity with AI governance, data-privacy, and compliance considerations for production of ML/LLM systems.
Signal-Driven Systems (nice-to-have): Exposure to intent-driven or signal-based product capabilities and event-driven system design.
Industry Experience (nice-to-have): Exposure to highly regulated industries like Financial Services, Legal & Healthcare.
Strong written and verbal communication, including technical writing skills. Fluent spoken English and ability to communicate with a remote, global team.
Ability to conduct cost/benefit analysis and business case development.

What We Offer
Remote-first work across Europe
Flexible working hours and a results-oriented culture
Company-provided work equipment
Compensation for work-related tools and subscriptions, including AI tools
Health insurance reimbursement for Ukrainians living abroad
50% reimbursement for job-related courses and professional development
Work in an international, distributed team
A high level of autonomy and ownership
A collaborative environment with direct access to cross-functional teams and leadership

Interested?
If this sounds like the kind of product challenge you’d like to take on, we’d be happy to hear from you. Apply and let’s talk about how your experience could fit Revenue Grid’s next stage of AI product development.