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At Teradata, we're not just managing data; we're unleashing its full potential. Our ClearScape Analytics™ platform and pioneering Enterprise Vector Store are empowering the world's largest enterprises to derive unprecedented value from their most complex data. We're rapidly pushing the boundaries of what's possible with Artificial Intelligence, especially in the exciting realm of autonomous and agentic systems. We’re building intelligent systems that go far beyond automation — they observe, reason, adapt, and drive complex decision-making across large-scale enterprise environments. As a member of our AI engineering team, you’ll play a critical role in designing and deploying advanced AI agents that integrate deeply with business operations, turning data into insight, action, and measurable outcomes.
Job Responsibility:
Design and implement autonomous AI agents for semantic search, text-to-SQL translation, and analytical task execution
Develop modular prompts, reasoning chains, and decision graphs tailored to complex enterprise use cases
Enhance agent performance through experimentation with LLMs, prompt tuning, and advanced reasoning workflows
Integrate agents with Teradata’s Model Context Protocol (MCP) to enable seamless interaction with model development pipelines
Build tools that allow agents to monitor training jobs, evaluate models, and interact with unstructured and structured data sources
Work on retrieval-augmented generation (RAG) pipelines and extend agents to downstream ML systems
Requirements:
5+ years of product engineering experience in AI/ML, with strong software development fundamentals
Proficiency with LLM APIs (e.g., OpenAI, Claude, Gemini) and agent frameworks such as AutoGen, LangGraph, AgentBuilder, or CrewAI
Experience designing multi-step reasoning chains, prompt pipelines, or intelligent workflows
Familiarity with agent evaluation metrics: correctness, latency, failure modes
Passion for building production-grade systems that bring AI to life
Master’s or Ph.D. in Computer Science, AI, or a related field, or equivalent industry experience
Experience working with multimodal inputs, retrieval systems, or structured knowledge sources
Deep understanding of enterprise data workflows and scalable AI architectures
Prior exposure to MCP or similar orchestration/protocol systems