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Teradata Logo Teradata · IT - Software Development

Senior AI Engineer

India, Hyderabad · Job Posted March 18, 2026
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Job Description

Teradata is building the next generation of AI-native analytics, enabling customers to deploy production-grade Generative AI systems directly where enterprise data lives. We are looking for a Senior AI Engineer to play a key role in designing and building Teradata’s vector store and retrieval infrastructure, powering RAG, multimodal AI, agentic workflows, and semantic search at enterprise scale.

Job Responsibility

  • Design and implement vector store capabilities integrated with Teradata’s analytics platform, including indexing, storage, retrieval, and query optimization
  • Build end-to-end RAG pipelines, including: Data ingestion and chunking strategies
  • Embedding generation and lifecycle management
  • Retrieval (dense, sparse, and hybrid search)
  • Context assembly and prompt orchestration
  • Develop and optimize semantic search algorithms and ranking strategies for enterprise workloads
  • Enable multimodal RAG (text, structured data, images, etc.) and agent-based workflows
  • Design agentic AI patterns, including tool calling, planning, memory, and orchestration
  • Implement guardrails for safety, reliability, and governance (hallucination mitigation, rounding, policy enforcement)
  • 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

Requirements

  • BS/MS/PhD in Computer Science, AI/ML, or a related field
  • 3+ years of software engineering experience with a strong focus on backend systems
  • Hands-on experience with vector databases or vector search systems
  • Practical experience building LLM-powered applications, especially RAG systems
  • 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

Nice to have

  • 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

What we offer

  • People-first culture
  • Flexible work model
  • Focus on well-being
  • Inclusive environment
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