Senior Product Manager, AI

About the role

What you'll do

• In this role, you will serve as a Senior Product Manager for Teradata's vector search and unstructured data capabilities, driving product vision, strategy, roadmap, execution, and adoption. You will define how enterprises turn documents, images, audio, and other unstructured content into searchable, trusted context that AI applications and agents can retrieve at scale, alongside the structured data they already manage in Teradata.
• On the retrieval side, you will own the product direction for vector and hybrid search: indexing and approximate nearest neighbor techniques, filtering, ranking and re-ranking, and the balance between recall, latency, freshness, and cost. You will work with engineering to make vector search a first-class, SQL-native capability that performs at enterprise scale and concurrency, and you will define how relevance and quality are measured, not only how fast queries run.
• On the ingestion side, you will own how unstructured data gets into the platform: connectors to object stores and enterprise content sources, document parsing, OCR, chunking, metadata extraction, embedding generation, and incremental refresh. You will shape pipelines that are reliable, governed, and cost-efficient, with access controls, lineage, and sensitive-data handling that carry through from source to retrieved result.
• Your impact will be measured by customers moving from retrieval-augmented generation (RAG) prototypes to production AI applications and agents that run on trusted enterprise data, with measurable gains in answer quality, time to value, and cost per query.
• Who You Will Work With
• You will collaborate with customers, engineering, the database engine and SQL teams, AI platform and data science teams, cloud infrastructure, UX, governance and security, product marketing, and field teams to bring next-generation retrieval capabilities into Teradata's enterprise ecosystem. You will be responsible for ensuring our products meet business objectives.
• What Makes You a Qualified Candidate
• Bachelor's in Engineering, Computer Science, or a related field from a recognized institution. MBA or advanced degree is a plus.
• 6+ years of experience in software product development companies, including 3+ years in product management working with AI/ML, search, or data platform products.
• Strong knowledge of embeddings and vector search, including index types (such as HNSW and IVF), quantization, filtered and hybrid search (keyword plus vector), and re-ranking.
• Working understanding of RAG, LLMs, and AI agents, and how retrieval quality drives answer quality. Experience defining evaluation metrics such as recall, precision, and relevance.
• Understanding of unstructured data ingestion: document parsing, OCR, chunking strategies, multimodal content, metadata extraction, and embedding pipelines, including GPU considerations.