AI-Enabled Revenue Operations Specialist

NavVis; München; On-site; EUR 90,000 - 130,000; Full time

Job summary

NavVis in Munich is building a Revenue Operations function designed for this moment. Not a back-office reporting team, but an operational intelligence engine at the heart of how we generate, convert, and grow revenue.

As our AI-Enabled Revenue Operations Specialist, you will own three interconnected missions: Revenue Insights & Reporting, Workflow Design & Optimization, and GTM Intelligence from Conversational & Behavioral Data.

Responsibilities

• Own three interconnected missions: Revenue Insights & Reporting, Workflow Design & Optimization, GTM Intelligence from Conversational & Behavioral Data.
• Build AI-enhanced analytics across the full funnel and forecast revenue to guide action weekly.
• Redesign lead-to-opportunity handover and deal-to-customer transitions to reduce friction.

Job description

The way B2B revenue teams operate is fundamentally reshaped by AI and most organizations haven’t caught up yet. The ones that move now won’t just be more efficient; they’ll see things their competitors can’t see, act on signals others miss, and compound that advantage quarter after quarter.

We're building a Revenue Operations function designed for this moment. Not a back-office reporting team, but an operational intelligence engine that sits at the heart of how we generate, convert, and grow revenue. This role is central to that ambition.

As our AI-Enabled Revenue Operations Specialist, you will own three interconnected missions:

• Revenue Insights & Reporting: Build AI-enhanced analytics across the full funnel, pipeline health, conversion dynamics, QBR narratives, revenue forecasting, turning fragmented data into decisions that leadership and frontline teams act on weekly, not quarterly.
• Workflow Design & Optimization: Redesign how our revenue teams actually work together, from lead-to-opportunity handover (BDS to AE), to deal-to-customer transition (AE to CSM), to strategic account intelligence and action. Eliminate the friction and information loss that slow deals down and erode customer experience.
• GTM Intelligence from Conversational & Behavioral Data: Analyze insights from customer and sales conversations (via conversation intelligence tools) and product usage patterns to surface what resonates by industry, customer segment, or buyer persona, and translate those patterns into actionable directives for GTM strategy, sales plays, and campaigns.

This is not a data engineering role and not a traditional reporting seat. Your primary job is to understand business problems across the end-to-end revenue lifecycle, where leads stall, where handovers lose context, where customer signals go unnoticed, and then build practical, AI-powered solutions that give our revenue teams an unfair advantage.

HOW YOU WILL MAKE AN IMPACT

Revenue Insights & Reporting

• Build and continuously improve funnel reporting across BDS, AE, and CSM stages, surfacing conversion rates, pipeline velocity, stage duration, and drop-off patterns that prompt action, not just observation.
• Prepare and automate QBR reporting packages that synthesize performance data, trends, and forward-looking indicators into narratives leadership can act on.
• Create revenue and bookings reports that connect pipeline activity to financial outcomes, supporting forecasting accuracy and resource allocation decisions.
• Use AI to accelerate insight generation, from automating data pulls and trend detection to generating draft narratives and anomaly alerts that would otherwise take days of manual analysis.

Workflow Design & Optimization

• Map, diagnose, and redesign the end-to-end lead-to-opportunity handover process between BDS and AE teams, eliminating information loss and reducing time-to-first-action.
• Design the deal-to-customer transition workflow from AE to CSM, ensuring account context, commitments, and expansion signals transfer cleanly into the post-sale motion.
• Build strategic account insight packages, AI-assisted briefs that combine CRM data, interaction history, usage patterns, and external signals into a single, actionable view for account teams.
• Collaborate with adjacent teams (Marketing, Customer Support) where workflows intersect, while keeping the primary focus on the BDS → AE → CSM spine.
• Leverage conversation intelligence tools (for example, Fathom, Gong, or similar) to identify patterns in buyer objections, competitive mentions, feature requests, and messaging effectiveness, broken down by industry, segment, or deal stage.
• Combine conversational insights with product usage and behavioral data to