About DAT
Job Application Deadline: 11/30/2026
The Opportunity
As a Sr AI Engineer, you're an integral part of the team who will 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
- Build and Ship: Write production code for the agentic services and platform components that power DAT's agentic mesh. This powers the systems our product and engineering counterparts build from.
- Deliver Against Specification: Build an approved specification which includes the problem, the non-goals, the non-functional budget, the trust boundary it crosses and deliver working software against it. Flag drift between what was asked for and what you were given before you write the first line, not after.
- Own Your Tests: Write the test suite for what you build including unit, integration, and evals from the specification itself, not from your own implementation, so a green suite means the requirement is met, not that the code agrees with itself. Your tests and observability are what raise, or cap, the repository's autonomy ceiling.
- Build Agentic Systems: Build and operate agents, tools, and multi-agent workflows on DAT's agent mesh which includes tool-calling, retrieval, memory, and orchestration that run inside the entitlements resolved for the request and never reach past them.
- AI Infrastructure on AWS: Build and operate production AI infrastructure on AWS — Bedrock,Agent Runtime Core, Strands, Lambda, S3, etc
- Design: You don't own the architecture, but you do own designs built from the premise. Bring informed pushback to decisions made by the team, flag what won't hold up in production, and show up to the conversation with an opinion, not just an implementation.
- Author Designs: Write the high-level design (HLD) for what you build. The design, the tradeoffs you made, and why so the next engineer, and the next team, can pick it up without you in the room.
- Review for Fidelity: Review AI-generated and human-written changes for the systems you own, holding the line on fidelity to the spec rather than on formatting, which is already settled by code.
- Respond to Incidents: Carry on-call for the services you build, investigate and resolve incidents in your own systems, and turn root cause into a fix rather than a postmortem slide.
- Publish What You Build: Put finished skills, agents, and components into DAT's capability marketplace so the next team that needs it finds it instead of rebuilding it.
The Skills and Experience You'll Bring
- 5+ years of experience in software engineering, with real production ownership and solutions you shipped, operated, and got paged for.
- Demonstrated experience building with LLMs and agentic frameworks in production: tool-calling, retrieval-augmented generation, multi-agent orchestration (e.g., LangGraph, Bedrock Agents, MCP-style tool integration) which shipped and operated, not a weekend prototype.
- Strong development skills in TypeScript/js, Python, Java, or Go, with the discipline to write tests other engineers actually trust.
- Solid, hands-on AWS experience: Bedrock,Agent Core Runtime, Strands, EKS/Kubernetes, Lambda, and S3 in production; working familiarity with Redpanda, MSK, or Kafka; comfortable in infrastructure-as-code (Pulumi, Terraform, or similar) even where you're not the one designing the account structure.
- Practical experience building or maintaining evaluation and monitoring for AI systems: eval sets, drift and quality signals, and treating a model regression with the same seriousness as a code regression.
- Comfortable working from a written specification rather than a verbal task. Ability to spot what's missing or ambiguous in a spec and push back before code, not after.
- Experience authoring design docs, HLDs, or short technical papers that another engineer can execute against without you there to explain it.
- Solid grounding in event-driven and distributed systems. You understand the tradeoffs Redpanda, MSK, kafka and relevant patterns force even if you're not the one drawing the topology.
- Working knowledge of observability practices — dashboards, traces, logs, and alerts sufficient to diagnose your own service and argue for what it needs to hit our authored autonomy tiers.
- Clear written and verbal communication — you'll be explaining tradeoffs to Staff and Principal engineers, to Product, and to non-technical stakeholders, not just to other engineers.
Bonus Skills
- Familiarity with A2A, MCP (Model Context Protocol), or comparable agent-interop patterns.
- Experience publishing to, or consuming from, an internal skill or agent registry / capability marketplace.
- Experience with model fine-tuning, distillation, or parameter-efficient training, and a clear point of view on when it beats prompting.
- 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
*This position is not eligible for visa sponsorship**
For Washington-based candidates, in compliance with the Washington State Pay Transparency Law, the salary range for this role is $162,000.00 - $207,000.00 + 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)
#LI-RF1
#LI-hybrid
Skills Required
- 10+ years of software engineering experience, including significant experience as a senior or staff engineer owning production infrastructure used by other engineering teams
- 4+ years building and operating machine learning or AI platforms, including taking models from notebooks into production and maintaining them
- Strong development skills in TypeScript/JavaScript, Java, or Go
- Extensive production AWS experience, ideally including EKS/Kubernetes, Lambda, Redpanda, MSK/Kafka, S3, and Secrets Manager
- Experience with infrastructure as code using Pulumi, Terraform, or similar tools
- Hands-on experience serving models at scale, including containerized inference, GPU scheduling, autoscaling, batching, and real-time, streaming, and batch scoring
- Production experience with LLM systems, including retrieval-augmented generation, vector databases, prompt and context management, tool calling or agent frameworks, and managed model APIs such as Amazon Bedrock
- Experience building model evaluation and monitoring systems, including offline evaluation sets, online metrics, drift detection, data quality checks, and regression criteria
- Strong background in event-driven and distributed systems using Redpanda, AWS MSK, or Kafka
- Experience with observability and on-call health, including dashboards, APM traces, logs, alerts, SLOs, and reducing incident frequency and MTTR
- Experience establishing engineering standards, including pull request and testing guidelines, deployment validation, model release criteria, and post-incident reviews
- Demonstrated technical leadership in cross-team system design, technical documentation, operations runbooks, and stakeholder alignment
- Proven mentoring experience helping engineers and data scientists develop system design, observability, and operational excellence skills
- Excellent communication skills with technical and non-technical stakeholders
- Experience with model fine-tuning, distillation, or parameter-efficient training
- Experience with marketplace, pricing, forecasting, or document extraction problems
- Freight, logistics, or supply chain domain experience
DAT Freight & Analytics Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about DAT Freight & Analytics and has not been reviewed or approved by DAT Freight & Analytics.
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Leave & Time Off Breadth — Time off appears comparatively strong, with generous PTO and paid holidays highlighted as a standout part of the overall package. Flexible schedules and hybrid/remote options further reinforce the sense of meaningful time-off and flexibility support.
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Retirement Support — Retirement support is positioned as a strength via 401(k) matching and immediate vesting on the match. An employee stock purchase plan is also presented as an additional long-term wealth-building lever.
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Healthcare Strength — Healthcare coverage is described as broad, spanning medical, dental, vision, disability, and mental health support. The depth of plan options is framed as a meaningful benefit even when overall compensation sentiment is less favorable.
DAT Freight & Analytics Insights
What We Do
DAT Freight & Analytics operates DAT One, North America’s largest truckload freight marketplace; Convoy Platform, an automated freight-matching technology; DAT iQ, the industry’s leading freight data analytics service; Trucker Tools, the leader in load visibility; and DAT Outgo, the freight financial services platform. Shippers, transportation brokers, carriers, news organizations, and industry analysts rely on DAT for market trends and data insights, informed by nearly 700,000 daily load posts and a database exceeding $1 trillion in freight market transactions. Founded in 1978, DAT is a business unit of Roper Technologies (Nasdaq: ROP), a constituent of the Nasdaq 100, S&P 500, and Fortune 1000. Headquartered in Beaverton, Oregon, with offices in Seattle, Denver, Springfield & Bangalore, DAT continues to set the standard for innovation in the trucking and logistics industry.
Why Work With Us
We pioneered freight technology and haven't stopped disrupting since. Our SaaS platform powers the supply chain that moves goods across America every day. What sets us apart: a teammate-first culture where we thrive on challenges and driving impact every day.
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