Sr AI Engineer

The Trade Desk The Trade Desk · Media · Bellevue, WA · Software Engineering

Senior AI Engineer role focused on designing, developing, and deploying internal AI solutions using LLMs, RAG, and agentic systems to improve productivity and streamline workflows within The Trade Desk. The role involves end-to-end ownership, collaboration with stakeholders, and AI enablement across the company.

What you'd actually do

  1. Design and deploy intelligent agentic systems that integrate large language models (LLMs) with enterprise data, tools, and workflows using frameworks like LangChain, LlamaIndex, and Semantic Kernel.
  2. Develop Retrieval-Augmented Generation (RAG) applications using tools like Azure AI Search, vector databases, and secure enterprise connectors to deliver contextual insights.
  3. Build and deploy agents using Microsoft Copilot, Copilot Studio, Anthropic Claude, and similar platforms to help teams operationalize solutions within enterprise guardrails.
  4. Build and iterate on conversational agents that solve real-world problems, meet stakeholder needs, and deliver measurable business value.
  5. Deliver high-impact features by collaborating across teams, leading through ambiguity, and aligning technical solutions with business goals.

Skills

Required

  • Python
  • LLM orchestration frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel)
  • prompt engineering
  • productionizing applications
  • CI/CD pipelines
  • data ingestion and transformation
  • APIs
  • ETL pipelines
  • connectors
  • vector databases
  • retrieval strategies
  • communication across technical and non-technical audiences
  • collaboration

Nice to have

  • C#
  • SQL
  • TypeScript/React
  • Azure AI Search
  • Microsoft Copilot
  • Copilot Studio
  • Anthropic Claude

What the JD emphasized

  • 1-2+ years working on AI-powered systems or products
  • productionizing applications
  • vector databases
  • retrieval strategies
  • agentic systems
  • LLM orchestration frameworks
  • prompt engineering

Other signals

  • building AI agents
  • integrating LLMs with enterprise data
  • productionizing AI applications