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Research Engineer – Agentic Platforms

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Teradata

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Location:
Mexico

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

The Office of the Chief Technology Officer (OCTO) is building the next generation of intelligent, agentic systems that leverage large language models (LLMs) to automate complex enterprise workflows. We seek a Research Engineer to design, build, and productionize multi-agent platforms that extend Teradata’s analytical capabilities into autonomous, AI-driven pipelines. This role sits at the frontier of applied AI research and platform engineering. You will work directly with state-of-the-art LLMs, agentic orchestration frameworks, and Teradata’s data ecosystem to create robust, scalable systems that enable autonomous reasoning, decision-making, and action across enterprise environments.

Job Responsibility:

  • Design and implement multi-agent systems that coordinate specialized LLM-powered agents to solve complex, multi-step analytical and operational tasks
  • Design agent orchestration patterns including task decomposition, inter-agent communication, tool use, memory management, and feedback loops
  • Build scalable agentic pipelines that integrate with Teradata’s data platform, enabling agents to query, analyze, and act on enterprise data autonomously
  • Design and manage LLM inference pipelines optimized for latency, throughput, and cost across cloud and on-premises deployments
  • Evaluate, benchmark, and select appropriate foundation models (open-source and proprietary) for specific agentic tasks within the Teradata ecosystem
  • Implement advanced prompting strategies including chain-of-thought, retrieval-augmented generation (RAG), and tool-augmented reasoning to maximize agent reliability and accuracy
  • Build and extend internal agentic SDKs and frameworks that enable research and product teams to rapidly develop and deploy agent-based applications
  • Integrate with leading agentic platforms and toolkits (e.g., LangChain, LlamaIndex, AutoGen, CrewAI, Anthropic Claude SDKs) and adapt them for enterprise-grade reliability
  • Develop reusable agent components, tool connectors, and evaluation harnesses that accelerate the path from prototype to production
  • Collaborate with research teams to translate cutting-edge LLM and agent research into production-ready platform capabilities
  • Work with product and service organizations to embed agentic workflows into Teradata’s customer-facing solutions
  • Communicate agentic system design, tradeoffs, and capabilities clearly to technical and non-technical stakeholders across multidisciplinary teams

Requirements:

  • Deep hands-on expertise with large language model APIs and inference frameworks (e.g., OpenAI, Anthropic, Mistral, vLLM, Ollama, HuggingFace Transformers)
  • Strong practical experience designing and building multi-agent systems using agentic SDKs and orchestration frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or equivalent
  • Proficiency in Python and experience building production-grade AI/ML services with clean, well-documented, testable code
  • Solid understanding of RAG architectures, vector databases (e.g., Pinecone, Weaviate, pgvector), and knowledge retrieval patterns
  • Experience with prompt engineering, LLM evaluation methodologies, and strategies for improving agent reliability and reducing hallucination
  • Familiarity with LLM inference optimization techniques including quantization, batching, caching, and model serving infrastructure
  • 5+ years of software engineering experience, with at least 2 years focused on LLM-based systems, agentic workflows, or applied AI research
  • Bachelor’s degree in Computer Science, Artificial Intelligence, or a related field, or equivalent demonstrated expertise
  • Proven track record designing and shipping multi-agent or LLM-powered systems into production environments
  • Experience collaborating across research and engineering teams to move from prototype to scalable, maintainable platform capability
  • Strong analytical and problem-solving abilities with meticulous attention to system reliability, agent behavior, and edge-case handling

Nice to have:

  • Experience building or contributing to agentic SDK frameworks or open-source LLM tooling
  • Familiarity with Model Context Protocol (MCP) or similar standards for tool-augmented LLM systems
  • Background with reinforcement learning from human feedback (RLHF), fine-tuning, or model alignment techniques
  • Experience with distributed systems and high-availability infrastructure for LLM serving at scale
  • Knowledge of AI governance, safety frameworks, and responsible deployment practices for autonomous agent systems
  • Prior work on AI/ML products within data warehousing, analytics, or enterprise software environments
What we offer:
  • People-first culture
  • Flexible work model
  • Focus on well-being
  • Inclusive environment

Additional Information:

Job Posted:
March 18, 2026

Employment Type:
Fulltime
Work Type:
Remote work
Job Link Share:

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