Applied AI Engineer I: AI Workflows & Data Quality

Daimler Truck North America LLC; Portland (OR); Hybrid; USD 71,000 - 91,000; Full time

Benefits offered by this job

401k company match up to 8%

4 weeks vacation

13+ holidays

Parental leave

Job summary

Daimler Truck North America is seeking a data-and-engineering oriented professional to strengthen the EQSC team's data lifecycle practices and connect design risk with manufacturing and field insights. You will translate AI-enabled concepts into useable workflows and help deploy data-driven solutions across engineering quality programs.

The role emphasizes collaboration with Vehicle Engineering, Product Engineering, Manufacturing, Quality, IT, and regional/global stakeholders, supporting

Qualifications

• 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 concepts, 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 software-development practices such as version control, configuration tracking, code review, testing discipline, and clear technical documentation.
• Evaluation and regression-testing mindset, including test case creation, result comparison, limitations documentation, and issue resolution.
• Familiarity with Jira, Azure DevOps, Confluence, SharePoint, or similar platforms.
• Basic awareness of automotive, engineering quality, product development, compliance, manufacturing, warranty, service, or field-quality workflows.

Responsibilities

• 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 configuring workflows, retrieval patterns, prompt examples, test cases, and deployment-support materials under senior guidance.
• Prepare approved standards, process guidance, historical examples, compliance references, investigation learnings, and engineering knowledge content for AI workflows.
• Help test, validate, and deploy AI-agent capabilities using enterprise platforms, Snowflake data assets, Microsoft 365 Copilot / Copilot Studio, APIs, and related tools.
• Capture data-quality issues, handoffs, duplicated steps, user pain points, pilot feedback, and improvement ideas in issue-tracking or backlog tools.
• Support analysis of connected engineering, compliance, investigation, manufacturing, service, warranty, and field data to improve risk assessment and product-quality decisions.
• Help measure AI-agent output quality, efficiency, token usage, user feedback, and accuracy by supporting evaluation datasets, regression testing, grounding checks, and stress testing.
• Create and maintain implementation notes, prompt/configuration logs, user guidance, training aids, data definitions, known limitations, and adoption content in Confluence/SharePoint.
• Collaborate with cross-functional teams and stakeholders to support user acceptance testing, adoption, and well-governed AI and data solutions.

Skills

SQL

Python

REST APIs

Snowflake

Education

Bachelor’s degree in engineering / CS / data science

Tools

Snowflake

SharePoint

Confluence

Jira

Azure DevOps

Power Platform

Job description

Daimler Truck North America is seeking a data-and-engineering oriented professional to strengthen the EQSC team's data lifecycle practices and connect design risk with manufacturing and field insights. You will translate AI-enabled concepts into useable workflows and help deploy data-driven solutions across engineering quality programs.

The role emphasizes collaboration with Vehicle Engineering, Product Engineering, Manufacturing, Quality, IT, and regional/global stakeholders, supporting