AI Engineer - II
Teradata · Posted Oct 8
Cloud data warehousing, analytics, and enterprise artificial intelligence services
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About the role
Teradata's Artificial Intelligence Engineering team builds foundational AI capabilities for Teradata's enterprise data platform, the Autonomous Knowledge Platform, which unifies data, knowledge and business context across on-premises, cloud, and hybrid environments. The team works across AI/ML, vector search, Retrieval-Augmented Generation (RAG), AI agents, and production software engineering. This role designs, builds, evaluates, and improves AI capabilities such as vector search and retrieval algorithms, RAG and Agentic RAG solutions, and AI agent components integrated with enterprise data and database workloads.
What you will do
- Design and implement AI/ML capabilities and intelligent applications for enterprise data and database workloads.
- Develop and enhance vector search and retrieval capabilities, including algorithms and techniques such as HNSW, IVF, Flat search, Product Quantization (PQ), and other vector indexing and quantization approaches.
- Develop Retrieval-Augmented Generation (RAG) and Agentic RAG solutions that combine enterprise data, vector search, large language models (LLMs), APIs, tools, and contextual information.
- Build components for AI agents and agentic workflows, including tool invocation, structured outputs, context management, MCP-based integrations, and multi-step workflows.
- Develop AI capabilities using Python, C++, Rust, or similar programming languages, with a focus on performance, scalability, maintainability, and platform independence.
- Build software that can operate across AWS, Azure, GCP, on-premises, and hybrid environments, minimizing dependencies on any specific cloud platform.
- Apply software engineering best practices including unit testing, integration testing, code reviews, observability, security, documentation, and performance optimization.
- Work with senior engineers and architects to translate product requirements and customer use cases into technical designs, implementation plans, and production-quality software.
- Contribute to technical investigations, prototypes, proof-of-concepts, and new AI capabilities as the technology and product landscape evolves.
- Continuously learn and apply emerging developments in Generative AI, LLMs, vector databases, agentic AI, information retrieval, model optimization, and AI engineering.
Skills used in this role
What the employer is looking for
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Computer Engineering, or a related technical field.
- 2+ years of professional software engineering, AI/ML, or data engineering experience, with hands-on development experience.
- Strong programming experience in at least one of C++, Python, Rust, Java, or a similar programming language.
- Experience building or integrating AI/ML, NLP, Generative AI, or LLM-based applications.
- Understanding of machine learning concepts, embeddings, information retrieval, vector search, and similarity search.
- Experience working with SQL, relational databases, structured data, or database-integrated applications.
- Experience developing software using APIs, microservices, SDKs, or distributed systems concepts.
- Understanding of software engineering fundamentals including data structures, algorithms, object-oriented/design principles, testing, debugging, and version control.
- Ability to analyze technical problems, investigate failures, and develop robust and maintainable solutions.
- Strong written and verbal communication skills, with the ability to collaborate effectively across engineering and cross-functional teams.
Preferred qualifications
- Hands-on experience with Generative AI, LLMs, RAG, Agentic AI, or AI application development.
- Familiarity with vector databases, vector indexes, embeddings, similarity search, or approximate nearest-neighbor (ANN) algorithms.
- Exposure to technologies such as HNSW, IVF, Product Quantization, or other vector search/optimization techniques.
- Experience with frameworks or technologies such as LangChain, LangGraph, MCP, agent frameworks, embedding models, vector databases, or similar AI frameworks.
- Experience working with structured and unstructured data ingestion and retrieval pipelines.
- Experience developing applications that run across multiple cloud platforms or cloud-agnostic environments is a plus.
- Understanding of AI observability, evaluation, testing, reliability, security, and responsible AI practices.
- Experience with Docker, Kubernetes, CI/CD, Linux, REST APIs, or distributed systems is a plus.
- Strong problem-solving mindset with the ability to work through ambiguous technical problems and learn new technologies quickly.
- Ability to work effectively in a collaborative engineering environment and take ownership of assigned technical deliverables from design through implementation and validation.
- A strong interest in keeping current with rapidly evolving AI/ML and Generative AI technologies and applying them to real-world enterprise problems.
Benefits and support
- Flexible work model where employees decide how, when, and where they work
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
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