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Added 2 mins ago
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DAT Solutions, LLC

Sr AI Engineer (Emerging AI)

Seattle, WA, United States

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Job details

Apply by: Nov 20, 2026
Experience: 10+ years of experience in software engineering, including significant time as a senior or staff engineer owning production infrastructure that other engineering teams depend on.
Posting language: English
Posted: Oct 20, 2026

Original job description

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 www.DAT.com Job Application Deadline: 11/30/2026 The Opportunity As a Sr AI Engineer, you'll build and own the platform that power our agentic solutions at DAT. Freight 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, SageMaker, 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, LLM-as-judge pipelines, A/B and shadow testing, and drift detection.
Cost and Performance: Own inference cost and latency as first-class metrics. Right-size GPU and serverless capacity, tune batching, caching, and quantization, and give teams clear visibility into what their workloads cost.
Safety and Governance: Implement guardrails, prompt and output logging, PII handling, access controls, and model and dataset lineage so AI systems meet our security and customer data commitments.
Best Practices: Drive the adoption of modern software development practices across AI work, including automated testing, code reviews, CI/CD pipelines, and infrastructure-as-code.
Mentorship: Mentor engineers and data scientists on production ML and distributed systems, and raise the operational bar of every team that builds on the platform.
Incident Management: Lead the response and resolution for complex production incidents involving AI services, perform root cause analysis, and implement preventative measures.

The Skills and Experience You'll Bring

10+ years of experience in software engineering, including significant time as a senior or staff engineer owning production infrastructure that other engineering teams depend on.
4+ years building and operating machine learning or AI platforms, with models you've taken from notebook to production traffic and then kept healthy.
Strong development language skills ideally using TypeScript/js, Java, or Go, with the software engineering discipline to build libraries other teams adopt willingly.

... For full info follow application link.DAT embraces the value of a diverse workforce, and believes it is a core strength of our company that we encourage those values in every DAT employee, at every level of our organization, regardless of tenure or rank. We provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state, and local laws.Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities

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More about this job

Skills

Leadership
AWS
Apache Kafka
Grading systems
Software development
Test automation
CI/CD
Infrastructure as code
ML
Root cause analysis
Machine learning
TypeScript
Oracle Java
Go

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