Staff PlatformOps Engineer (Emerging AI)

DAT Freight Solutions; Seattle (WA); Hybrid; USD 198,000 - 246,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

AD&D Insurance

401k matching

Employee Stock Purchase Plan

Paid time off

Transit benefits

Job summary

DAT Freight & Analytics is seeking a Staff AI Platform Engineer to own the platform for all AI/ML workloads. You will set architectural direction for model gateway, inference, feature storage, and observability across the organization.

You will lead AI system architecture, drive alignment with Product and Engineering, and build scalable, production-grade infrastructure on AWS. This role emphasizes mentorship and incident management while delivering high-impact ML platforms.

Qualifications

• 10+ years of software engineering experience with production infrastructure ownership.
• 4+ years building and operating ML/AI platforms end-to-end.
• Strong development skills in TS/Node.js, Java, or Go; ability to ship reusable libraries.
• Extensive AWS experience with production systems including EKS, Lambda, S3, and managed services.
• Hands-on experience deploying models at scale: GPU scheduling, batching, and real-time vs batch tradeoffs.
• Practical experience with LLM systems in production and vector databases.
• Proven experience building evaluation/monitoring for models; defining regression criteria.
• Experience mentoring engineers and data scientists; raising the operational bar.

Responsibilities

• Platform Ownership: Design, build, and operate shared services for models including a model gateway and inference endpoints.
• Technical Leadership: Lead architecture for large-scale AI systems and align across teams on how models are built and shipped.
• Cloud Architecture: Architect scalable AI infra on AWS (Bedrock, SageMaker, EKS, Kafka, S3) with IaC.
• Evaluation and Quality: Build offline/online evaluation, regression tests, drift detection.
• Cost and Performance: Manage inference cost, latency, and resource sizing (GPU, batching, caching).
• Safety and Governance: Implement logging, access controls, data lineage, and governance gates.
• Best Practices: Promote CI/CD, automated testing, and infrastructure-as-code across AI projects.
• Mentorship & Incident Management: Mentor teams and lead post-incident review and prevention.

Skills

Senior/Staff engineering leadership

AWS production systems

TypeScript/Node.js

LLM systems in production

Model deployment & inference

IaC: Pulumi/Terraform

Vector databases

Monitoring & observability

Kafka/MSK

Mentoring engineers

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

SageMaker

Bedrock

EKS/Kubernetes

S3

Pulumi

Terraform

Kafka/MSK

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:

10/31/2026

The Opportunity

As a Staff AI Platform Engineer, you'll build and own the platform that every AI and machine learning workload at DAT runs on. 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 set the architectural direction for that platform, from the model gateway and inference layer through feature and vector storage, evaluation harnesses, and production observability. 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/Node.js, Java, or Go, with the software engineering discipline to build libraries other teams adopt willingly.


• Extensive AWS experience with production systems, ideally including EKS/Kubernetes, Lambda, Redpanda, MSK/Kafka, S3, and Secrets Manager, plus infrastructure-as-code with Pulumi, Terraform or similar.


• Hands-on experience serving models at scale: containerized inference, GPU scheduling, autoscaling, batching, and the tradeoffs between real-time, streaming, and batch scoring.


• Practical experience with LLM systems in production, including retrieval-augmented generation, vector databases, prompt and context management, tool-calling or agent frameworks, and managed model APIs such as Amazon Bedrock.


• Proven experience building evaluation and monitoring for models, not just services: offline eval sets, online metrics, drift and data quality checks, and a clear definition of what "regression" means for a model.


• Strong background in event-driven and distributed systems using Redpanda, AWS MSK or Kafka


• Fluency with observability and on-call health, designing dashboards, APM traces, logs, and alerts, defining SLOs, and using these tools to drive down incident frequency and MTTR.


• Experience establishing and raising engineering standards for a team: PR and testing guidelines, deployment validation checklists, model release criteria, and post-incident review practices.


• Demonstrated technical leadership: leading cross-team designs in ambiguous problem spaces, writing clear system design documents and operations runbooks, and driving alignment across Engineering, Product, and Operations.


• Proven mentoring track record, especially helping engineers and data scientists grow in system design, observability, and operational excellence.


• Excellent communication skills, with the ability to explain trade-offs and system behavior clearly to engineers, product managers, and non-technical stakeholders.

We'd be Extra Excited if You Have

• Experience with model fine-tuning, distillation, or parameter-efficient training, and a clear point of view on when it beats prompting.


• Background in marketplace, pricing, forecasting, or document extraction problems.


• Freight, logistics, or supply chain domain experience.

Why DAT?

DAT is an award winning employer of choice.

For starters, we have a hybrid work environment, but we also know what makes a great workplace. We have a time-tested and resolute set of operating values predicated on integrity, mutual respect, open communication, and executing with excellence. These values inform our strategic vision as much as any one of our products does. We've been an employer of choice in the Portland metropolitan area for four decades, and within one year of opening our Denver office, DAT was #26 on Built In Colorado's 100 Best Places to Work In Colorado.

• Medical, Dental, Vision, Life, and AD&D insurance


• Parental Leave


• Flexible Vacation Time (FVT)


• An additional 10 holidays of paid time off per calendar year


• 401k matching (immediately vested)


• Employee Stock Purchase Plan


• Short- and Long-term disability sick leave


• Flexible Spending Accounts


• Health Savings Accounts


• Employee Assistance Program


• Additional programs - Employee Referral, Internal Recognition, and Wellness


• Free TriMet transit pass (Beaverton Office)


• Competitive salary and benefits package


• Work on impactful projects in a cutting-edge environment


• Collaborative and supportive team culture


• Opportunity to make a real difference in the trucking industry


• Employee Resource Groups

For Washington-based candidates, in compliance with the Washington State Pay Transparency Law, the salary range for this role is $198,000.00 - $246,000.00 + target bonus. DAT considers factors such as scope and responsibilities of the position, candidate's work experience, education and training, core skills, internal equity, and market and business elements when extending an offer.

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

The contractor will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor's legal duty to furnish information. 41 CFR 60-1.35(c)