Sr. Director of Product Management, CX Insights

Description

About Birdeye
Birdeye is the leading agentic marketing platform for multi-location brands.

Companies like H&R Block, Aspen Dental, and Caesars Entertainment use Birdeye to manage marketing across thousands of locations — from how they get found, to how they convert, to how they retain customers. Our platform replaces disconnected point tools with AI agents that execute work at the location level — responding to reviews, updating listings, publishing content, and driving conversions.

Backed by Marc Benioff, Jerry Yang, and Accel-KKR, Birdeye was named to G2’s 2026 Best Agentic AI Products list — appearing alongside the world’s leading AI companies. We’re expanding rapidly into enterprise, with growing adoption across large, multi-location brands.

Senior Director of Product, CX Insights

Location: United States

Employment Type: Full-time

About the Role

Birdeye is building the next generation of tools that help businesses interact with and serve their customers through actionable intelligence and drive tangible outcomes.

We’re looking for a Senior Director of Product to lead, scale, and define our CX Insights vision and product organization. This is a product leadership role combining global product strategy, team leadership, strategic customer engagement, conversational analytics, and AI-native product innovation.

You should understand how multi-location enterprise businesses transform customer experience using the voice of customers across multiple channels, and be excited about building products in a rapidly evolving category. 

What You’ll Own

CX Insights Strategy & Vision

• Lead overall vision, product strategy, and multi-year roadmap for CX Insights products (including customer analytics, feedback aggregation, automated workflows, text analytics, and enterprise conversational analytics).
• Define company-wide standards for how enterprise businesses measure, analyze, and elevate customer interactions and experience.
• Develop capabilities around customer resolution rates, analytics accuracy, sentiment tracking, transcriptions, competitive benchmarking, and emerging CX analytics signals.
• Turn complex conversational behavior, real-time data streams, and large interaction datasets into simple, actionable experiences for business operators and marketers.
• Identify opportunities to move beyond basic analytics into proactive customer workflows, automated responses, and multi-channel follow-ups.

Organizational Leadership & Scaling

• Build, mentor, and scale a high-performing product management team driving CX Insights initiatives.
• Establish product management excellence, operational rigor, and AI-first product development methodologies across the team.
• Partner closely with executive leadership to align product strategy with company-wide revenue and growth objectives.

Customer & Market Development

• Work directly with enterprise customers to understand how they currently handle inbound/outbound communications, customer feedback, and service interactions.
• Partner with C-suite and executive leaders at enterprise customer accounts to shape their AI-driven customer experience strategies.
• Serve as executive sponsor for strategic CX Insights customer accounts and key industry partnerships.
• Lead customer discovery, demos, and working sessions around CX Insights capabilities.
• Identify emerging customer problems before they become obvious product categories.
• Separate durable customer needs from short-term trends in a rapidly changing market.

AI-Native Product Development

• Champion an AI-first product culture, leveraging AI tools extensively for research, market analysis, competitive intelligence, data analysis, prompt engineering, and product discovery.
• Rapidly build POCs and prototypes using AI-assisted development tools and frameworks to validate high-impact ideas before committing engineering resources.
• Use AI to generate PRDs, conversational flows, evaluation benchmarks, acceptance criteria, test cases, and edge cases.
• Work closely with engineers in an AI-led development environment, using AI coding and testing tools to explore technical approaches and accelerate execution.

Data & CX Infrastructure

• Partner with Engineering and Data teams on the systems required to process, analyze, and optimize real-time customer data streams and conversations at scale.
• Develop a deep understanding of LLM latency, text/speech model accuracy, streaming data protocols, and the technical challenges of delivering high-quality customer experience platforms reliably.
• Establish meaningful operational and product metrics (e.g., resolution rate, customer satisfaction, sentiment accuracy, latency, analytics precision) as the CX Insights ecosystem evolves.

Requirements

What You Bring

• 10+ years of product leadership experience, with a proven track record of scaling product teams and portfolios in CX Insights, Conversational AI, Customer Analytics, or Enterprise SaaS.
• Proven experience building, mentoring, and scaling high-performing product management teams in fast-growing, high-tech environments.
• Experience building software for verticals such as Automotive, Healthcare, Dental, or Home Services is a plus.
• Strong understanding of CX Insights, Customer Analytics, AI Agents, LLMs, text/speech processing, and scalable data architecture.
• Proven experience building data-driven B2B SaaS products for enterprise customers.
• Strong technical fluency with APIs, data pipelines, analytics, and AI/ML concepts.
• Comfortable working directly with enterprise customers and leading executive product discovery.
• Demonstrated ability to leverage AI tools for research, requirements, analysis, prototyping, and POCs.
• Comfortable collaborating with engineers in an AI-assisted development environment.
• Strong product judgment and ability to operate effectively with incomplete information.
• Based in the United States.

Experience That Stands Out

•  CX Insights / Customer Analytics / Conversational AI
• Customer Experience platforms / Automation
• Real-time data processing and analytics tuning
• Customer feedback analytics, sentiment analysis, and transcript summarization
• LLM or generative AI