Principal Engineer, Semantic Platforms and Graph Intelligence

** 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*
* We are seeking a world-class Principal Knowledge Graph Engineer to lead the architecture, development, and evolution of next-generation knowledge graph platforms that power AI, reasoning, discovery, and autonomous decision-making at enterprise scale for Teradata Context Engine.

This role is intended for a recognized technical leader who has built and operated very large-scale knowledge graphs comprising billions of entities, relationships, events, documents, and embeddings derived from both structured and unstructured data. You will own, and drive innovation at the intersection of graph technologies, semantic modeling, information retrieval, machine learning, agents, and generative AI for Teradata Context Engine, our Autonomous Knowledge Platform.

Context Engine is a platform that converts enterprise data estates into governed, agent-ready knowledge. Built for organizations where AI reliability and auditability are non-negotiable, Context Engine enables companies to deploy AI workflows on the data they already own - without rebuilding their infrastructure, without retraining their models, and without waiting for generic AI synthesis to learn the business terminology that took their analysts years to master.

Technical Leadership

+ Define and execute the long-term vision for enterprise knowledge graph architecture and graph-enabled AI systems.

+ Lead the design of highly scalable graph platforms supporting billions of nodes and edges across multiple data domains.

+ Establish standards, frameworks, and best practices for graph modeling, ontology design, semantic interoperability, and graph lifecycle management.

+ Serve as the company's senior technical authority on graph technologies, semantic systems, and knowledge representation.

Knowledge Graph Architecture

+ Design and implement large-scale knowledge graphs that integrate:

+ Structured enterprise data

+ Semi-structured data

+ Documents and content repositories

+ Event streams

+ APIs and external data sources

+ Embedding and vector representations

+ LLM-generated knowledge artifacts

+ Develop scalable entity resolution, identity graph, and record-linkage frameworks.

+ Build semantic layers that unify business concepts across disparate systems.

AI, Retrieval & Reasoning

+ Design hybrid retrieval architectures combining:

+ Knowledge graphs

+ Vector databases

+ Full-text search

+ Semantic retrieval

+ Agentic workflows

+ Enable GraphRAG and graph-enhanced AI experiences.

+ Develop graph-based reasoning systems that support explainable AI and autonomous decision-making.

+ Apply graph algorithms, network analysis, and graph machine learning to generate insights and predictions.

Engineering & Platform Development

+ Build distributed graph ingestion and processing pipelines for large-scale enterprise environments.

+ Optimize graph performance, storage, indexing, partitioning, caching, and query execution.

+ Implement graph observability, quality assurance, lineage, governance, and monitoring capabilities.

+ Contribute production-grade code and lead the development of reusable graph services and platforms.

Industry Leadership

+ Stay at the forefront of advancements in:

+ Knowledge graphs

+ Semantic technologies

+ Graph databases

+ Graph machine learning

+ Retrieval systems

+ AI agents

+ Large and small language models

+ Publish technical papers, patents, blogs, conference talks, and thought leadership where appropriate.

+ Mentor senior engineers and influence architecture across the organization.

+ A plus would be in-depth knowledge in at least one vertical, such as Healthcare, Finance, etc.

** Who You'll Work With*
* You will work hands-on across the full lifecycle of graph systems, from ontology engineering and graph construction to retrieval, reasoning, embeddings, graph machine learning, and AI-powered applications. This is not a management role. We are looking for a builder, architect, and technical thought leader who can design systems, write code, solve hard problems, and influence strategy.

** What Makes…