This is a deeply hands-on technical leadership role for a recognized expert in Natural Language Processing who combines strong research foundations with proven experience shipping production systems that serve millions of users and process billions of documents. You will work at the intersection of large language models, information retrieval, knowledge graphs, semantic understanding, and agentic AI.
The ideal candidate has a track record of driving breakthrough NLP capabilities from research to production and possesses deep expertise across classical NLP, modern transformer architectures, retrieval-augmented generation (RAG), multimodal understanding, information extraction, and large-scale language model systems.
Technical Leadership
Define and execute the strategic roadmap for NLP and language understanding capabilities across our Knowledge Platform.
Serve as the technical authority for large-scale NLP architecture, algorithms, and production deployment.
Drive innovation in enterprise language understanding, semantic search, retrieval systems, knowledge extraction, and AI reasoning.
NLP and Language Intelligence
Design and build advanced NLP systems for
Entity extraction
Relationship extraction
Information extraction
Document understanding
Semantic indexing
Context understanding and representation
Text classification
Topic modeling
Summarization
Question answering
Conversational AI
Knowledge grounding
Multi-document reasoning
Extracting context from multi-modal sources of language
Multi-lingual solutions
Machine translation
Develop systems that transform unstructured enterprise content into structured knowledge assets.
Advance techniques for long-context understanding, document intelligence, and multi-hop reasoning.
Build domain-adaptive language understanding models across diverse enterprise data sources.
Develop solutions with highest quality and performance
Develop solutions that are tested and validated
Large Language Models
Design and optimize applications built on frontier foundation models.
Build advanced retrieval-augmented generation architectures for enterprise-scale environments.
Develop agentic workflows that leverage LLMs for planning, reasoning, execution, and tool usage.
Create evaluation methodologies that measure factuality, grounding, trustworthiness, and task completion.
Improve model performance through prompt engineering, fine-tuning, continued pretraining, synthetic data generation, and reinforcement-learning-based approaches.
Knowledge and Semantic Systems
Design NLP pipelines that power enterprise knowledge graphs and semantic layers.
Develop ontology-aware language understanding systems.
Build entity resolution, canonicalization, taxonomy mapping, and concept extraction capabilities.
Connect language understanding with graph-based reasoning and enterprise knowledge discovery platforms.
Platform and Scale
Build highly scalable distributed NLP systems processing petabytes of enterprise content.
Optimize inference architectures for latency, throughput, cost efficiency, and reliability.
Lead deployment strategies across on-prem, cloud-native, hybrid, and enterprise environments.
Partner closely with platform engineering teams to operationalize NLP services at global scale.
Research and Innovation
Stay at the forefront of advances in
Foundation models
Agentic AI
Retrieval systems
Representation learning
Deep learning
Knowledge-enhanced language models
Reasoning systems
Publish, patent, contribute to open source, and represent the organization externally at premier AI conferences and industry events.
Mentor senior engineers and help establish NLP engineering best practices across the company.
Who You’ll Work With
Partner with distinguished engineers, architects, researchers, and product leaders to shape the future of Teradata enterprise AI.
What Makes You a Qualified Candidate
PhD or MS in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, NLP, or related field.
12+ years of software engineering experience, including 8+ years building production NLP and machine learning systems.
Recognized industry leader in Natural Language Processing, Language AI, Search, Retrieval, or LLM-based systems.
Deep hands-on expertise developing and deploying large-scale NLP systems in production.
Deep Expertise In
Transformer architectures
Large Language Models
Retrieval-Augmented Generation (RAG)
Semantic search
Information retrieval
Knowledge extraction
Entity recognition
Relation extraction
Text understanding
Conversational AI
Machine learning
Deep learning
Representation learning
Graph-enhanced NLP
Vector search systems
Knowledge graphs
Strong Programming Skills
Python
PyTorch
TensorFlow/JAX
Spark
Distributed computing frameworks
Experience With
Hugging Face ecosystem
Fine-tuning and adaptation frameworks
Large-scale model evaluation
Vector databases
Embedding models
Search engines
Knowledge graphs
Distributed ML infrastructure
AI observability and evaluation platforms
Preferred Qualifications
PhD with published research in NLP, IR, ML, or AI in top-tier peer reviewed journals and conferences
Experience building systems that serve hundreds of millions of users or process billions of documents.
Contributions to major NLP open-source ecosystems.
Publications in ACL, EMNLP, NAACL, COLING, NeurIPS, ICML, ICLR, KDD, SIGIR, WWW, or related venues.
Experience leading architecture for enterprise copilots, intelligent assistants, or autonomous agents.
Expertise in enterprise search and knowledge management systems.
Experience with graph-based reasoning and knowledge graph technologies.
Patent portfolio in NLP, machine learning, search, or language understanding.
What You’ll Bring
Established reputation as an industry expert in NLP and language AI.
Proven record of taking breakthrough research into production at scale.
Experience building state-of-the-art systems involving
Enterprise search
Enterprise copilots
Document intelligence
Retrieval systems
Knowledge extraction
AI agents
Semantic reasoning
Knowledge graphs
Ability to influence technical strategy across multiple organizations.
Strong balance of scientific rigor, engineering excellence, and product impact.
Success Metrics
Within 12 months, you will
Define next-generation NLP and language intelligence architecture for the platform.
Deliver measurable improvements in retrieval quality, answer accuracy, grounding, and user satisfaction.
Establish world-class evaluation and benchmarking frameworks.
Lead development of enterprise-scale knowledge extraction and semantic understanding capabilities.
Enable agentic AI experiences that leverage enterprise knowledge with high trust, transparency, and precision.
Raise the organization's NLP and AI capabilities to industry-leading levels.
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 committed to actively working to foster an inclusive environment that celebrates people for all of who they are
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