Job description

Our company At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. What You’ll Do In this role, you will lead the product strategy and execution for Teradata’s AI platform capabilities, with a focus on helping enterprises move from AI experimentation to trusted, governed, production-scale AI. You will shape the roadmap across Teradata VantageCloud Lake, ClearScape Analytics, AI Unlimited, ModelOps, LLMOps, enterprise vector capabilities, and open ecosystem integrations that enable customers to build, deploy, monitor, and scale AI/ML, generative AI, and agentic AI use cases on trusted enterprise data. Success in this role requires a product leader who can translate rapidly evolving AI market needs into differentiated platform capabilities, customer value, and measurable business outcomes. You will define how Teradata enables customers to prepare data, train models, operationalize AI pipelines, integrate with leading LLM providers, manage model governance, and activate AI-driven insights at enterprise scale while maintaining performance, cost efficiency, openness, and trust. • Own and champion the product vision, strategy, and roadmap for Teradata’s AI platform portfolio, including VantageCloud Lake, ClearScape Analytics, AI Unlimited, ModelOps, LLMOps, enterprise vector capabilities, and AI/ML lifecycle management • Define platform capabilities that enable customers to build, test, deploy, monitor, and govern AI/ML, generative AI, and agentic AI solutions using trusted enterprise data • Partner with engineering, architecture, data science, cloud, security, and go-to-market teams to translate AI strategy into scalable product execution • Lead and develop a global team of product managers responsible for roadmap definition, prioritization, customer discovery, launch readiness, and product adoption • Engage with customers, field teams, partners, and executive stakeholders to identify AI platform use cases, adoption barriers, market opportunities, and competitive differentiation • Drive product decisions around open ecosystem interoperability, including Python, Jupyter, open table formats, cloud data lakes, external model providers, open-source models, and leading cloud LLM services • Shape capabilities that support in-database analytics, feature engineering, model training, model deployment, real-time scoring, vector search, retrieval-augmented generation, and governed AI operations • Establish clear success metrics for adoption, usage, time to value, revenue impact, customer outcomes, platform performance, and AI workload efficiency • Create compelling product narratives that connect Teradata’s AI platform capabilities to business value, trusted AI, operational scale, and differentiated enterprise outcomes • Influence organization-wide priorities that accelerate adoption of Teradata’s AI platform and strengthen Teradata’s market position in enterprise AI, analytics, and data platforms Who You’ll Work With You will lead a global product management team and work closely with engineering, architecture, data science, cloud platform, security, customer success, sales, partners, and executive leadership. This team is responsible for advancing Teradata’s AI platform strategy and enabling customers to operationalize AI on trusted, governed data at enterprise scale. As the AI Platform Product Management Leader, you will provide strategic product direction, market insight, and execution discipline to align Teradata’s AI innovation with customer needs and business growth. What Makes You a Qualified Candidate • Proven experience leading product strategy for enterprise AI, analytics, data platforms, cloud platforms, or AI/ML infrastructure • Demonstrated success defining and scaling platform products that drive customer adoption, revenue growth, and measurable business outcomes • Strong understanding of AI/ML lifecycle management, ModelOps, LLMOps, generative AI, agentic AI, vector search, retrieval-augmented generation, and enterprise AI governance • Experience with cloud data platforms, data lakes, open table formats, Python-based analytics workflows, Jupyter notebooks, APIs, and integrations with open-source or cloud-native AI services • Ability to translate complex technical capabilities into clear product strategy, customer value, go-to-market positioning, and executive-level decision frameworks • Advanced degree in a relevant field such as Computer Science, Data Science, Engineering, Business Analytics, or equivalent practical experience What You’ll Bring • Executive-level communication skills with the ability to align technical teams, business leaders, customers, and field organizations around a clear AI platform strategy • Deep awareness of enterprise AI market trends, including trusted AI, governed AI operations, generative AI, agentic AI, AI-ready data, cloud economics, and open ecosystem interoperability • Strong product judgment across data preparation, feature engineering, in-database analytics, model training, model deployment, model monitoring, vector capabilities, and production AI operations • A strategic, outcome-based mindset focused on customer adoption, differentiated value, platform scalability, cost efficiency, and measurable business impact • Experience building repeatable product operating rhythms, including roadmap governance, prioritization frameworks, launch readiness, adoption tracking, and escalation paths • Ability to lead through influence across global teams and create strong partnerships with engineering, field, marketing, customer success, partners, and executive stakeholders • Customer-first orientation with the ability to turn market signals, competitive insights, and enterprise AI adoption patterns into actionable product direction As the AI Platform Product Management Leader, you will help define how Teradata enables the next generation of enterprise AI. Your work will directly shape the capabilities customers use to experiment faster, operationalize trusted AI, integrate with modern AI ecosystems, and scale production AI workloads across the enterprise. Why We Think You’ll Love Teradata We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are an anti-racist company because our dedication to Diversity, Equity, and Inclusion is more than a statement. It is a deep commitment to doing the work to foster an equitable environment that celebrates people for all of who they are. #LI-CP2

Requirements

Must-haves

What You’ll Do
Define platform capabilities that enable customers to build, test, deploy, monitor, and govern AI/ML, generative AI, and agentic AI solutions using trusted enterprise data
Partner with engineering, architecture, data science, cloud, security, and go-to-market teams to translate AI strategy into scalable product execution
Lead and develop a global team of product managers responsible for roadmap definition, prioritization, customer discovery, launch readiness, and product adoption
Engage with customers, field teams, partners, and executive stakeholders to identify AI platform use cases, adoption barriers, market opportunities, and competitive differentiation
Drive product decisions around open ecosystem interoperability, including Python, Jupyter, open table formats, cloud data lakes, external model providers, open-source models, and leading cloud LLM services
Shape capabilities that support in-database analytics, feature engineering, model training, model deployment, real-time scoring, vector search, retrieval-augmented generation, and governed AI operations
Establish clear success metrics for adoption, usage, time to value, revenue impact, customer outcomes, platform performance, and AI workload efficiency
Create compelling product narratives that connect Teradata’s AI platform capabilities to business value, trusted AI, operational scale, and differentiated enterprise outcomes
Influence organization-wide priorities that accelerate adoption of Teradata’s AI platform and strengthen Teradata’s market position in enterprise AI, analytics, and data platforms
Who You’ll Work With
What Makes You a Qualified Candidate
Proven experience leading product strategy for enterprise AI, analytics, data platforms, cloud platforms, or AI/ML infrastructure
Demonstrated success defining and scaling platform products that drive customer adoption, revenue growth, and measurable business outcomes
Strong understanding of AI/ML lifecycle management, ModelOps, LLMOps, generative AI, agentic AI, vector search, retrieval-augmented generation, and enterprise AI governance
Experience with cloud data platforms, data lakes, open table formats, Python-based analytics workflows, Jupyter notebooks, APIs, and integrations with open-source or cloud-native AI services
Ability to translate complex technical capabilities into clear product strategy, customer value, go-to-market positioning, and executive-level decision frameworks
Advanced degree in a relevant field such as Computer Science, Data Science, Engineering, Business Analytics, or equivalent practical experience
What You’ll Bring
Executive-level communication skills with the ability to align technical teams, business leaders, customers, and field organizations around a clear AI platform strategy
Deep awareness of enterprise AI market trends, including trusted AI, governed AI operations, generative AI, agentic AI, AI-ready data, cloud economics, and open ecosystem interoperability
Strong product judgment across data preparation, feature engineering, in-database analytics, model training, model deployment, model monitoring, vector capabilities, and production AI operations
A strategic, outcome-based mindset focused on customer adoption, differentiated value, platform scalability, cost efficiency, and measurable business impact
Experience building repeatable product operating rhythms, including roadmap governance, prioritization frameworks, launch readiness, adoption tracking, and escalation paths

Nice-to-haves

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