Applied AI Engineer I

Daimler Truck North America is building practical, well-governed AI capabilities with its Engineering Quality, Safety and Compliance (EQSC) team. This hybrid role in Portland, OR helps strengthen data lifecycle practices and connects design risk assessment with manufacturing and field insights. You will support governed data pipelines and AI-agent workflows, including evaluation and deployment-support activities.

Compensation: USD 71,000 - 91,000 per year.

Schedule: Hybrid (4 days per week in-office / 1 day remote).

What you drive at DTNA

• Support governed data pipelines, including Snowflake-enabled datasets, by preparing, cleaning, validating, and connecting requirements, specifications, validation records, vehicle compliance inputs, defect investigations, manufacturing data, service data, warranty information, and field-quality insights.
• Assist with SQL queries, data models, metadata fields, and data-quality checks to improve traceability, reliability, and readiness for analytics and AI-assisted workflows.
• Contribute to AI-agent implementation by helping configure workflows, retrieval patterns, prompt examples, test cases, and deployment-support materials under guidance from senior team members.
• Prepare approved standards, process guidance, historical examples, compliance references, investigation learnings, and engineering knowledge content for use in AI-assisted workflows and evaluation datasets.
• Help test, validate, and deploy AI-agent capabilities using approved enterprise platforms, Snowflake-enabled data assets, Microsoft 365 Copilot / Copilot Studio, APIs, and related tools.
• Capture data-quality issues, manual handoffs, duplicated steps, user pain points, pilot feedback, and improvement ideas in issue-tracking or backlog tools.
• Support analysis across connected engineering, compliance, investigation, manufacturing, service, warranty, and field data to improve risk assessment, product-quality decisions, corrective-action follow-up, and service diagnostics.
• Help measure AI-agent output quality and efficiency, including token usage and user feedback, by supporting evaluation datasets, regression testing, grounding checks, stress testing, and hallucination-reduction reviews.
• Create and maintain implementation notes, prompt and configuration change logs, user guidance, training aids, data definitions, known limitations, and adoption content in Confluence, SharePoint, and similar enterprise knowledge platforms.
• Collaborate with Vehicle Engineering, Product Engineering, Vehicle Compliance, Product Validation, Manufacturing, Service, Quality, IT, defect investigation teams, and regional/global stakeholders to support user acceptance testing, adoption, and well-governed AI and data solutions.

Requirements

• Bachelor’s degree in engineering, computer science, data science, or a related technical field.
• 0–2 years of relevant experience through work, internships, co-ops, academic projects, or applied technical projects.
• Foundational understanding of AI/ML and GenAI, including large language models, embeddings, retrieval, prompt patterns, and basic model evaluation.
• Awareness of responsible AI practices, including grounding, hallucination reduction, privacy, access control, bias awareness, and human review for high-impact engineering decisions.
• Basic experience preparing, cleaning, validating, joining, and documenting datasets for analytics, automation, or AI-assisted workflows.
• Working knowledge of SQL, Python, REST APIs, and enterprise data-platform concepts, including Snowflake or similar environments.
• Familiarity with basic software-development practices such as version control, configuration tracking, code review, testing discipline, and clear technical documentation.
• Evaluation and regression-testing mindset, including the ability to create test cases, compare expected and actual results, document limitations, and support issue resolution.
• Familiarity with collaboration, documentation, and issue-tracking tools such as Jira, Azure DevOps, Confluence, SharePoint, or similar platforms.
• Basic awareness of automotive, engineering quality, product development, compliance, manufacturing, warranty, service, or field-quality workflows.
• Ability to communicate clearly, collaborate across functions, learn quickly, ask good questions, and manage multiple tasks with guidance.

Technology you will use

• Snowflake, SQL, Python, REST APIs
• Microsoft 365 Copilot, Copilot Studio, APIs
• Confluence, SharePoint, Jira, Azure DevOps
• Power BI, Excel, Power Platform

Benefits

• 401k company contribution with company match up to 8%
• Non-elective company contribution of 3–7% depending on age
• Starting at 4 weeks paid vacation
• 13+ calendar holidays
• 8 weeks paid parental leave
• Employee assistance program
• Comprehensive healthcare plans and wellness programs
• Onsite fitness (at some locations)
• Tuition assistance
• Volunteer paid time off
• Short-term and long-term disability plans

Additional information

• Relocation assistance is not available.
• This position is not open for Visa sponsorship or to existing Visa holders.
• Applicants must be legally authorized to work permanently in the country where the position is located at the time of application.
• Final candidates must successfully complete a criminal background check and may be required to complete a pre-employment drug screen.
• EEO - Disabled/Veterans.

DTNA provides a scheduled posting end date to support candidate application planning. This schedule reflects the latest plans and is subject to change; postings may be extended or removed earlier than expected.