Senior Data & AI Engineer

Daimler Truck North America • Portland, OR

1d • Hybrid

About The Position

This senior individual contributor role focuses on building, validating, and enabling artificial intelligence, machine learning, and automation solutions across Daimler Truck North America (DTNA). The engineer works hands-on with business teams to develop solutions, help teams own and sustain them, and turn prototypes into governed, production-ready implementations in partnership with IT and platform teams. The role also serves as a technical reference for the Business Data Analytics Team (BDAT) and DTNA, advancing data- and AI-informed decision-making and sharing effective practices across the organization.

BDAT, within the Continuous Improvement department, serves as DTNA’s enterprise Center of Enablement for self-service data, analytics, automation, and AI. The role helps cultivate a collaborative, inclusive, and continuously improving data-driven culture by building reusable solution patterns, testing emerging technologies, advising business units on appropriate approaches, and coaching practitioners through hands-on co-development and training.

The position is hybrid, with four days per week in the office and one remote day, and is open to applicants who can work in or relocate to Fort Mill, South Carolina, or Portland, Oregon. Relocation assistance is not available. The stated starting salary range is $117,000–$150,000 USD, dependent on knowledge, skills, and experience. The position is not open to visa sponsorship or existing visa holders.

Requirements

• Bachelor’s degree and at least 5 years of relevant experience, or 8 years of relevant experience in lieu of a degree.
• Advanced proficiency in Python and SQL, including writing, reviewing, testing, and productionizing code and checking AI-generated output for accuracy.
• Demonstrated experience designing, building, and deploying AI/ML, automation, or data solutions beyond the prototype stage and into production.
• Hands-on experience building with LLMs and agentic approaches, with sound judgment about when these approaches are appropriate and a commitment to continuous learning.
• Strong grounding in machine learning and statistical methods.
• Hands-on experience with cloud data platforms such as Snowflake, including data modeling, extraction, transformation, loading, and API integrations.
• Working knowledge of DevOps practices, including version control, automated testing, and continuous integration and delivery pipelines.
• Ability to coach and co-develop with teams at all organizational levels and translate between business and technical audiences, including executives.
• 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; a pre-employment drug screen may also be required.

Nice To Haves

• Degree in business, mathematics, computer science, statistics, analytics, or a related quantitative field.
• Master’s degree in a quantitative field, or a data science certification or equivalent.
• Experience with MLOps, including model monitoring and maintenance.
• Experience with governance, cost management, or usage transparency for cloud data and AI platforms.
• Experience designing or delivering training and upskilling programs.
• Familiarity with BI and automation tools such as Power BI, Tableau, Alteryx, or Power Platform.
• Experience scoping and leading time-boxed engagements, including managing scope, timelines, dependencies, and stakeholders.
• Familiarity with Continuous Improvement principles and methods, including recognizing when a process should be standardized before building a technical solution.
• Experience in manufacturing, automotive, or transportation industries.

Responsibilities

• Design, build, and deploy AI/ML, agentic, and automation solutions for high-impact, complex business initiatives, co-developing with business teams and translating business objectives into working solutions and proofs of concept.
• Move promising prototypes into governed, production-ready solutions with IT, the Data Intelligence Hub, and business-embedded data teams, using continuous integration and delivery pipelines, automated testing, and documentation.
• Build reusable solution patterns, including ways to connect business data to conversational AI tools, so proven solutions can be adopted by multiple teams.
• Develop new ways of working with data, analytics, automation, and AI, and share best practices across DTNA.
• Support Continuous Improvement colleagues in developing data, analytics, automation, and AI solutions for CI programs.
• Serve as a technical reference for BDAT and DTNA on AI engineering, data platforms, and best practices.
• Partner with IT and the Data Intelligence Hub to evaluate, pilot, and integrate self-service analytics, automation, and AI tools and platforms.
• Work with IT and platform teams on data connections, APIs, access and governance, usage and cost transparency, and auditing of self-service environments.
• Stay current with emerging data and AI trends, test technologies hands-on, and recommend what DTNA should adopt and when.
• Lead hands-on coaching and co-development across business units, helping teams solve problems and build their own tangible solutions.
• Coach teams in applying data, analytics, automation, and AI to their Continuous Improvement work, and provide technical consultation for unique business challenges.
• Mentor junior team members and data community practitioners.
• Collaborate with senior leadership, IT, the AI Center of Excellence, and the enterprise data community to advance a data- and AI-driven culture and promote self-service capabilities.
• Advise business units on suitable approaches—including AI/ML, automation, analytics, or BI—and recommend simpler solutions when appropriate.
• Identify opportunities to apply data, analytics, and AI to strategic initiatives and challenge established ways of working when technology suggests a better approach.
• Foster an engaged data and AI community through collaboration, knowledge sharing, and best practices.
• Participate in community events, including the annual DT Week conference, workshops, and hackathons.

Benefits

• Annual bonus program.
• 401(k) company contribution with company match up to 6%, plus a non-elective company contribution of 3–7% depending on age.
• Starting at four weeks of paid vacation.
• 13 or more calendar holidays.
• Eight weeks of paid parental leave.
• Employee assistance program.
• Comprehensive healthcare plans.
• Wellness programs.
• Onsite fitness at some locations.
• Tuition assistance.
• Paid volunteer time off.
• Short-term and long-term disability plans.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior