VP, Product Management

Uniphore is one of the largest B2B AI-native companies—decades-proven, built-for-scale and designed for the enterprise. The company drives business outcomes, across multiple industry verticals, and enables the largest global deployments.
Uniphore infuses AI into every part of the enterprise that impacts the customer. We deliver the only multimodal architecture centered on customers that combines Generative AI, Knowledge AI, Emotion AI, workflow automation and a co-pilot to guide you. We understand better than anyone how to capture voice, video and text and how to analyze all types of data.
As AI becomes more powerful, every part of the enterprise that impacts the customer will be disrupted. We believe the future will run on the connective tissue between people, machines and data: all in the service of creating the most human processes and experiences for customers and employees.
Job Description:
Job Description: VP, Product Management
The Vice President of Data Products is responsible for overseeing the vision, strategy, and execution of the company’s data platforms. Our data platforms play multiple roles, including:
As internal capabilities, they power our GenAI stack (access, transform, and supply for GenAI model training data), our CDP product and our applications
As customer-facing products, they provide Zero-ETL access to Enterprise data and a rich suite of capabilities to connect, clean, orchestrate and operationalize data
Our Zero Data AI Cloud, positioned around the concept of being able to leverage Enterprise data more quickly and flexibly than any other approach, is anchored on this suite of data platforms that this role will inherit and expand.
This is the GM of the Data Product business and ensures the development and delivery of innovative data products and solutions that align with business objectives, enhance decision-making and create competitive advantages. The VP leads cross-functional teams to design, build, and maintain scalable data products, deliver on revenue goals, and while fostering a data-driven culture.
Key Responsibilities
Strategic Leadership
Define and execute the strategic roadmap for data platforms, aligning with the company’s business goals, financial outcomes, and customer needs.
Develop and execute a data readiness strategy to support internal activities aligned with thewhich align with the Engineering and AI organization's architecture approaches and andsupport Customer discovery and insights from their’s AI goals.
Collaborate with executive leadership to identify and prioritize data innovation, AI use cases, and monetization that require high-quality, accessible, and reliable data products.
Build and communicate a vision for how data products can deliver business value and drive growth.
AI Data Readiness
Ensure that all data platforms provide robust capabilities, assets are for cleaning, annotated, structured, and optimized for AI and machine learning purposes.
Drive the adoption of modern data management practices, including data labeling, feature engineering, and real-time data streaming for AI within Uniphore and supporting sales during customer interactions.
Partner with data scientists and engineers to define requirements and participate with Engineering and Architecture teams in designing scalable AI pipelines and MLOps workflows.
Deep LLM & Generative AI Architecture
Deep understanding of Large Language Models (LLMs) and Generative AI architectures, including transformer-based models, embeddings, prompt/context engineering, model selection, fine-tuning, RAG, and the tradeoffs between proprietary and open-source models.
Agentic AI & AI Application Architecture
Expertise in emerging agentic AI architectures, including AI agents, tool/function calling, orchestration, memory, multi-agent systems, workflow automation, and human-in-the-loop patterns, with the ability to translate these capabilities into scalable enterprise products.
AI Evaluation, Reliability & Production Optimization
Deep understanding of evaluating and operationalizing AI/LLM systems in production, including model and application evaluation, quality measurement, latency, cost/performance optimization, observability, model drift, feedback loops, and continuous improvement.
AI Safety, Security & Responsible AI
Strong understanding of enterprise AI safety, security, and responsible AI practices, including AI governance, model risk, prompt injection, data leakage, bias, privacy, guardrails, access controls, explainability, and human oversight.
Product Management for Data Platforms
​Lead the high-level design and collaborate with AI Engineering and Data Engineering Leadership, define development, and deployment of scalable requirements, user-centric data products and platforms.
Prioritize product features and enhancements based on customer feedback, market trends, and business needs for monetization Ensure the use of best practices in data science, analytics, and engineering in product design.
Oversee the creation and deployment of data products, including training datasets, feature stores, and synthetic data generation tools, that enable AI innovation.
GTM experience working with Sales, performing competitor analysis, pricing, experience working with Product Marketing and partner teams on expanding product growth and delivering on revenue targets
Ability to define a product roadmap, prioritize feature, functionality, and capabilities that are needed by customers, based on the competitive landscape, analyst reports, etc.​
Team Leadership