Top Tech Jobs & Startup Jobs

Contribute to designing, operating, and scaling reliable distributed systems within DAT’s SRE platform team. Responsibilities include troubleshooting incidents, implementing monitoring and automation, capacity planning, performance tuning, infrastructure-as-code, cloud migration, reliability initiatives, and on-call support. The role collaborates with software engineers and architects, promotes SRE best practices, and helps modernize legacy systems using cloud platforms and infrastructure tooling.

Leads application development strategy, engineering teams, technical projects, and operational excellence. Partners with Product, UX, DevOps, and Data Science teams to deliver scalable logistics features, maintain reliable high-availability services through code reviews, automated testing, and CI/CD, resolve production issues, and hire, mentor, and retain engineering talent.

Own the architecture and operation of DAT’s shared AI and machine learning platform. Build model gateways, inference services, feature and vector storage, evaluation systems, observability, governance, and cost controls on AWS. Lead distributed-systems and cloud architecture, production incident response, engineering standards, cross-functional alignment, and mentorship. Support model training, serving, monitoring, safety, and continuous improvement across AI teams.

Own buyout agreement execution, pricing and promotional exceptions, and HubSpot sales workflows. Coordinate across Operations, Sales, and RevOps; maintain accurate CRM records; review aging and pricing reports; support retention efforts; and ensure processes, documentation, and follow-ups remain accurate and timely.

Owns end-to-end deal approval, pricing governance, and contract lifecycle management for Broker, Carrier, and Shipper segments. The role establishes deal desk SLAs and Delegation of Authority frameworks, integrates contracting across Salesforce and NetSuite, redesigns self-signup and enterprise workflows, and partners with Sales, Finance, Legal, and Product. It also provides pricing analytics, investigates deal performance issues, maintains approval records, and develops scalable operating procedures.

Own the strategy, roadmap, and delivery of DAT’s TMS integrations and public and partner-facing APIs. Define integration priorities, modernize legacy SOAP and FTP connectivity, establish API governance and monetization models, manage vendor relationships, coordinate cross-functional dependencies, and build the business case for reliable, scalable integration infrastructure.

Manages customer experience operations for fintech products, leading onshore and offshore support teams, performance metrics, vendor relationships, workforce planning, collections workflows, escalations, automation, and AI initiatives. Partners with Product, Engineering, Operations, Risk, Finance, and Data to improve carrier support, operational efficiency, and product launches. The role is hybrid in Seattle and requires three days onsite weekly.

Lead product development for DAT’s freight analytics and intelligence platform. Represent shippers, brokers, and carriers in product decisions; conduct customer and market research; manage analytics and pricing features from discovery through launch; collaborate cross-functionally; lead product rollouts; and monitor product health, engagement, and customer outcomes.

Lead the Fintech Platform engineering team building and scaling a reliable ledger, fintech products, banking and lender integrations, and financial systems for trucking businesses. Coach and develop engineers, establish accountability, guide speed-versus-quality tradeoffs, and promote engineering excellence. The role requires expertise in payments, systems of record, cloud platforms, and data systems, with preferred experience in double-entry accounting, asset-based lending, marketplaces, and banking integrations.

Develop and operate business intelligence and AI-agent solutions for strategic decision-making. Own KPIs, dashboards, reports, data models, and ad hoc analyses; translate ambiguous business questions into recommendations; identify automation opportunities; validate data quality; and monitor and improve deployed agents. Partner with leadership and cross-functional teams across Operations, Finance, Product, Marketing, and Data Engineering while documenting capabilities and enabling responsible adoption.