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Sr AI Engineer; Emerging AI

Job in Seattle, King County, Washington, 98127, USA
Listing for: DAT Freight & Analytics
Full Time position
Listed on 2026-10-16
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Backend Developer
Salary/Wage Range or Industry Benchmark: 162000 - 207000 USD Yearly USD 162000.00 207000.00 YEAR
Job Description & How to Apply Below
Position: Sr AI Engineer (Emerging AI)
About DAT

DAT Freight & Analytics is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of freight and logistics innovation for nearly five decades. Founded in 1978, DAT operates the largest freight marketplace in North America - processing 250 million+ load posts annually and maintaining one of the largest repositories of freight market transaction data in the world.

On a defined path to $1 billion in revenue, DAT deploys a suite of software solutions, machine learning models, and intelligent automation tools that help brokers, carriers, and shippers price freight accurately, source capacity, reduce risk, and operate more efficiently. With nearly 700 teammates across offices in Denver, CO;
Portland, OR;
Seattle, WA;
Springfield, MO;
Toronto, ON; and Bangalore, India, DAT combines the credibility of a multi-decade market leader with the drive of a company that is not done disrupting the industry it helped build. For more information, visit

About DAT

DAT Freight & Analytics is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of freight and logistics innovation for nearly five decades. Founded in 1978, DAT operates the largest freight marketplace in North America - processing 250 million+ load posts annually and maintaining one of the largest repositories of freight market transaction data in the world.

On a defined path to $1 billion in revenue, DAT deploys a suite of software solutions, machine learning models, and intelligent automation tools that help brokers, carriers, and shippers price freight accurately, source capacity, reduce risk, and operate more efficiently. With nearly 700 teammates across offices in Denver, CO;
Portland, OR;
Seattle, WA;
Springfield, MO;
Toronto, ON; and Bangalore, India, DAT combines the credibility of a multi-decade market leader with the drive of a company that is not done disrupting the industry it helped build. For more information, visit

Job Final date to receive applications: 11/30/2026

The Opportunity

As a Sr AI Engineer, you'll build and own the platform that power our agentic solutions ight is an uncertain business, and the models we ship reduce that uncertainty: rate forecasts, load-to-truck matching, document extraction, fraud signals, and the agentic workflows our brokers and carriers use to move freight faster. None of that reaches a customer without a platform that makes training, serving, evaluating, and monitoring models routine instead of heroic.

You'll help build the platform, from the model gateway and inference layer through feature and vector storage, evaluation harnesses, production observability, agentic framework (A2A) all on a spine based on secure access and utilization. This is a highly visible role for an engineer who wants their work multiplied across every AI team in the company.

What You'll Do
  • Platform Ownership:
    Design, build, and operate the shared services that engineers and business users use to ship models: a model gateway for LLM access, inference endpoints for real-time and batch scoring, feature storage, vector search, and a common SDK.
  • Technical Leadership:
    Lead architecture for large-scale AI systems, write the design documents, and drive alignment across Product, and Engineering and Business users on how models get built and shipped at DAT.
  • Cloud Architecture:
    Architect and run scalable, reliable AI infrastructure on AWS, including Bedrock, Sage Maker, EKS, Redpanda, MSK (Kafka), Lambda, and S3, all defined in Pulumi.
  • Evaluation and Quality:
    Build the offline and online evaluation systems that tell us whether a model or prompt change is an improvement, including regression suites,…
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