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The Trade Desk — New York, England
The Trade Desk is a global technology company and the world’s leading independent platform for digital advertising, with nearly 4,000 employees across more than 30 offices. Our technology helps advertisers reach the right audiences across the open internet — from streaming TV and podcasts to mobile apps, news, and more. Advertising powers the content people love.
By making it more transparent, effective, and responsible, we help support trusted journalism, quality entertainment, and creators worldwide. The world’s brands and agencies rely on us to reach their customers and grow their businesses responsibly. The scale of our platform brings unique technical challenges — from processing massive datasets in real time to building systems that operate reliably on a global scale.
When you work here, your impact is worldwide. We welcome diverse perspectives, encourage curiosity, and build teams that learn from one another. If you’re driven to solve meaningful challenges, we’d love to meet you.
What we do: GTM Engineering builds the internal products and AI systems that make our sellers, traders, and account teams faster and sharper — from sprint and pipeline dashboards to agentic assistants that prep a rep before a call or flag a deal at risk before it slips. We sit at the intersection of engineering, data, and revenue strategy, shipping tools that directly move the needle on revenue growth and sales productivity.
What You'Ll Do
: Architect and build agentic systems that automate and augment GTM workflows — pipeline hygiene, account research, call prep, deal risk scoring, forecasting, and rep coaching — using LLM orchestration frameworks( Ex: LangGraph ). Define the agentic platform strategy for the pod: agent design patterns, tool-calling conventions, retrieval-augmented pipelines, evaluation frameworks, and human-in-the-loop guardrails for revenue-critical workflows. Integrate core GTM systems (Salesforce, Outreach, ZoomInfo, Slack, and The Trade Desk's own platform data) as agent-accessible tools and data sources via internal data platforms and MCP-style interfaces.
Set the technical bar for the pod — reviewing designs, establishing engineering standards, and leading architectural reviews across the GTM Engineering roadmap. Partner directly with Product, Sales, Trading, and RevOps leadership to translate agentic capability into measurable outcomes — pipeline velocity, forecast accuracy, rep ramp time, and sales productivity — and mentor engineers in the pod on AI-first thinking.
Who You Are
: BS degree in Engineering related discipline and 8+ years of software engineering experience, with at least 2 years building production LLM or agentic applications (agents, RAG pipelines, tool-use, multi-agent orchestration). Deep fluency in Python and TypeScript/JavaScript, with hands-on experience in agentic frameworks — LangChain/LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar. Strong command of enterprise integration patterns: REST/GraphQL APIs, event-driven architecture, and connecting SaaS GTM platforms (CRM, sales engagement, data enrichment) programmatically.
Experience building full-stack applications end to end — from data pipelines and backend services to the front-end tools sellers and traders actually use daily. Track record as a technical lead: driving architectural decisions, writing RFCs, and raising the quality bar across a team without relying on management authority.
Nice To Have
: Prior experience in Sales/RevOps tooling, GTM engineering, or internal tooling domains — especially in ad tech, media, or programmatic advertising. Familiarity with Salesforce, Outreach, Gainsight, or similar GTM platforms — especially via API or integration layer. Experience evaluating and red-teaming LLM agents for safety, reliability, and correctness in revenue-critical business contexts.
Exposure to media buying, campaign performance data, or advertising analytics.