Applied AI Engineer I — AI-Driven Data & Quality Workflows

Daimler Truck North America LLC

Portland (OR)

Hybrid

USD 71,000 - 91,000

Full time

3 days ago

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Benefits offered by this job

401k with company match up to 8%

4 weeks paid vacation

13+ holidays

8 weeks parental leave

Healthcare plans

Job summary

Daimler Truck North America LLC in Portland, OR is seeking a data/AI-enabled workflow engineer within the EQSC team to improve data lifecycles and connect design risk with manufacturing and field insights.

You will help deploy data models, support AI-enabled workflows, and collaborate across Vehicle Engineering, Product Validation, Manufacturing, Service, and IT to drive quality improvements and governance.

Qualifications

Bachelor’s degree in engineering, computer science, data science, or 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 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.

Responsibilities

Support governed data pipelines, including Snowflake-enabled datasets, by helping prepare, clean, validate, and connect 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 that 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 to support practical workflow improvements.
Support analysis of connected engineering, compliance, investigation, manufacturing, service, warranty, and field data to help improve risk assessment, product-quality decisions, corrective-action follow-up, and service diagnostics.
Help measure AI-agent output quality, efficiency, token usage, user feedback, and accuracy by supporting evaluation datasets, regression testing, grounding checks, stress testing, and hallucination-reduction reviews.
Create and maintain implementation notes, prompt/configuration change logs, user guidance, training aids, data definitions, known limitations, and adoption content in Confluence, SharePoint, and similar enterprise knowledge platforms.
Work 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.