Principal Product Manager - Customer Service Suite

About Lucidya

Lucidya is an AI-native platform for customer experience (CX) intelligence that manages entire customer life cycles autonomously, from initial engagement through retention and growth. Unlike platforms that only surface insights and leave the action to you, Lucidya completes the loop with proprietary NLU capabilities developed entirely in-house and trained on millions of multilingual conversations, equipping marketing, support, CX, and research teams to deliver personalized experiences that drive measurable improvements in customer satisfaction, retention, and lifetime value.

Customer service is evolving faster than ever. Customers expect instant, personalized support, while support teams are under constant pressure to resolve issues faster without sacrificing quality. AI is fundamentally changing how support organizations operate, and we're building the products that will define that future.

As our Principal Product Manager, you'll own the strategy and direction of Lucidya's Customer Service Suite, including Omni Serv, our ticketing and case management platform, mobile experience, and the AI-powered capabilities that enable support teams to work smarter.

This isn't a role where you'll simply manage a backlog. You'll define where the product goes, make difficult prioritization decisions, and shape experiences that thousands of users rely on every day. You'll spend time with customers, understand how they actually work, and turn those insights into products that solve meaningful problems.

We're looking for someone who enjoys solving complex challenges, questions assumptions, and is excited by building products where AI creates real customer value - not simply because it's the latest trend.

• Own the vision, strategy, and roadmap for Lucidya's Customer Service Suite, ensuring every investment moves the product closer to solving meaningful customer problems.
• Spend time with customer support teams, operations leaders, and enterprise customers to deeply understand how they work, where they struggle, and what would genuinely improve their day-to-day experience.
• Work closely with Engineering and Design to continuously deliver valuable improvements, favouring learning through iteration over waiting for perfection.
• Make thoughtful product decisions by balancing customer needs, business priorities, technical complexity, and long-term platform strategy.
• Champion AI-powered experiences that genuinely improve agent productivity and customer outcomes, rather than adding technology for technology's sake.
• Partner with Customer Success, Sales, and Marketing to ensure new capabilities are successfully adopted and create measurable business impact after launch.
• Use customer feedback, product analytics, market trends, and experimentation to continuously improve the product and validate product decisions.
• Create alignment across stakeholders by communicating product strategy, priorities, trade-offs, and roadmap decisions with clarity and confidence.
• Build trust across cross‑functional teams by creating a collaborative environment where great ideas can come from anyone.

• You've spent 7-9 years building B2B SaaS products and have owned a product or product suite end‑to‑end—not just individual features.
• You enjoy solving customer problems more than shipping features. You naturally ask "What problem are we solving?" before deciding "What should we build?"
• You're comfortable making difficult prioritization decisions and explaining the reasoning behind them, even when not everyone agrees.
• You enjoy spending time with customers and believe the best product decisions come from understanding real user behaviour rather than assumptions.
• You collaborate exceptionally well with engineers and designers. You don't need to write production code, but you're technical enough to challenge ideas, understand trade‑offs, and make informed decisions together.
• You're naturally curious. Whether it's a new AI capability, workflow automation tool, or emerging technology, you've probably already experimented with it before someone asked…