Staff AI Engineer
Teradata · Posted Oct 2
Cloud data warehousing, analytics, and enterprise artificial intelligence services
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About the role
Teradata's Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context, and the company is building the next generation of AI-native analytics so customers can deploy production-grade Generative AI systems where their enterprise data lives. The team works on vector store and retrieval infrastructure that powers RAG, multimodal AI, agentic workflows, and semantic search at enterprise scale, collaborating with AI architects, ML engineers, and domain experts in Silicon Valley. This Staff AI Engineer role owns the architecture and technical direction of the vector store and retrieval stack, defines design patterns for RAG and agentic AI, and builds evaluation frameworks and core indexing, storage, retrieval, and API capabilities.
What you will do
- Own the architecture and technical direction of Teradata’s vector store and retrieval stack.
- Define design patterns and best practices for RAG, semantic search, and agentic AI systems.
- Lead technical design reviews and influence cross-team architectural decisions.
- Identify scalability, performance, and reliability risks and drive solutions proactively.
- Design agentic AI patterns, including tool calling, planning, memory, and orchestration.
- Design and implement core vector store capabilities, including indexing strategies, storage layouts, retrieval algorithms, and APIs.
- Build and maintain RAG evaluation frameworks, including relevance, faithfulness, accuracy, and cost metrics.
- Collaborate with product, research, and platform teams to translate customer use cases into scalable features.
- Benchmark Teradata’s vector store and RAG capabilities against industry alternatives (e.g., cloud and open-source solutions).
- Contribute to technical design reviews, architecture decisions, and long-term AI platform strategy.
Skills used in this role
What the employer is looking for
- BS/MS/PhD in Computer Science, AI/ML, or a related field.
- 8+ years of professional software engineering experience, including ownership of complex systems.
- Deep expertise in vector search, information retrieval, or semantic search systems.
- Proven experience designing and deploying production-grade RAG platforms.
- Strong understanding of: Embeddings and similarity search Data chunking and context optimization Dense vs sparse vs hybrid retrieval Semantic search and relevance ranking
- Proficiency in Python (and/or Java); experience with production-grade systems.
- Experience working with large-scale data and performance-sensitive systems.
Preferred qualifications
- Experience with multimodal embeddings and retrieval.
- Familiarity with agent frameworks (e.g., LangChain, LangGraph, or equivalent).
- Experience implementing AI guardrails and evaluation frameworks.
- Exposure to cloud platforms (AWS, Azure, or GCP).
- Experience with distributed systems or analytics platforms.
- Open-source contributions or published work in AI, IR, or GenAI.
Benefits and support
- Flexible work model
About Teradata
Teradata is a global enterprise software company specializing in multi-cloud data warehousing, analytics, and artificial intelligence solutions. Its flagship offerings, including Teradata VantageCloud and ClearScape Analytics, help organizations turn enterprise data into trusted, autonomous actions. The company serves leading global enterprises across industries such as financial services, retail, healthcare, and telecommunications.
- Industry
- Software
- Company size
- 5000-10000 employees
- Founded
- 1979
- Location
- San Diego, California, USA
- Funding stage
- Public Company
Leadership
President and Chief Executive Officer
John Ederer
Chief Financial Officer
Louis Landry
Chief Technology Officer
Sumeet Arora
Chief Product Officer
Michael Hutchinson
Chief Operating Officer
Recent coverage
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