AI Integration Engineer

Daimler Truck North America

AI Integration Engineer shaping engineering processes with AI-driven solutions at Daimler Truck. Collaborating with multidisciplinary teams to enhance specifications and improve automation in testing.

Posted 6/11/2026full-timePortland • Oregon • 🇺🇸 United StatesJuniorMid-LevelWebsite

About the role

Key responsibilities & impact

Apply AI‑based tools and agent‑driven workflows to optimize how engineering specifications are authored, reviewed, and standardized
Design and implement mechanisms to expand standardized specifications into automatically generated test cases for HiL and vehicle‑level testing
Integrate AI‑assisted test generation into existing software tooling developed by the team, ensuring compatibility with established validation pipelines
Incorporate Large Language Models (LLMs) into the software tool development lifecycle to improve documentation quality, code review effectiveness, and overall user experience
Collaborate with system, software, and test engineering teams to ensure AI‑enabled tooling aligns with real‑world engineering workflows and validation needs
Define and maintain technical concepts, architectures, and roadmaps for AI integration within internal software tools
Validate and verify AI‑enabled tooling through reviews, experimentation, and targeted testing to ensure reliability, traceability, and scalability
Identify technical risks and limitations related to AI usage and provide clear reporting, recommendations, and mitigation strategies
Define the data and measurable indicators needed to evaluate virtual driver systems on DTNA vehicles against DTNA performance standards, including ODD expansion rate, incident reporting, remote assistance activity, system capability, and in-service performance. Establish apples-to-apples assessment criteria for VD partners by benchmarking autonomous performance against Cascadia durability, maintenance intervals, fuel efficiency, and vehicle uptime to ensure solutions deliver incremental customer value on DTNA platforms
Contribute lessons learned and best practices to influence future tooling standards and development approaches across the organization

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Software Engineering, or a related engineering discipline and 2+ years of relevant experience is required
Strong software engineering fundamentals, including experience building and maintaining internal tools or developer‑facing applications
Experience working with or integrating AI systems, such as LLMs, agent frameworks, or AI‑assisted development tools
Familiarity with test automation concepts, including HiL, SiL, or vehicle‑level testing environments
Ability to translate loosely defined engineering needs into structured, scalable software solutions
Demonstrated ability to work effectively across multidisciplinary engineering teams
Strong sense of ownership, curiosity, and initiative within your technical domain
Ability to communicate complex technical concepts clearly to both technical and non‑technical audiences
Commitment to continuous learning and staying current with evolving physical autonomy, AI, and software development practices
An attached resume is required.

Benefits

Comp & perks

Relocation assistance is not available for this position

ATS Keywords

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Hard Skills & Tools

AI systemsLarge Language Models (LLMs)test automationHiL testingSiL testingsoftware engineeringdeveloper-facing applicationsinternal toolssoftware solutionsvalidation pipelines

Soft Skills

collaborationcommunicationownershipcuriosityinitiativecross-disciplinary teamworktranslating engineering needscontinuous learningreportingproblem-solving

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in Software EngineeringBachelor’s degree in related engineering discipline