Inside the Role
The DTNA Data Intelligence Hub builds AI and data analytics solutions that enable our customers to be faster, safer, and more profitable, transforming DTNA into the intelligent company of tomorrow. By leveraging data from all business functions, including massive amounts of vehicle and automation telematics data, we develop data and AI solutions to improve our products, streamline manufacturing, and perfect our customers' experience.
In this exciting and challenging role as the DIH Data-AI Tech Lead, you will drive the development of innovative new data and AI products using DTNA’s and Daimler Truck’s data foundation along with emerging AI technology. You are a highly motivated candidate who is willing to quickly learn and understand new technologies and tools. You will deliver solutions using the scale of our data and platforms to support your product needs, and look for new opportunities in the evolving world of AI to bring to our data.
This role is responsible for driving data technical architecture, AI solution implementation, and cross-region collaboration. In addition to the existing responsibilities in the current position, the role has evolved to include a significant AI component, including ensuring the enterprise's platforms, pipelines, and data assets are AI-ready — enabling the rapid, responsible development and scaling of AI products in partnership with the business. This is an AI-first role: the architect is expected to default to AI-enabled approaches wherever they add value, and to continuously evaluate emerging AI technology across the data stack and surrounding ecosystem.
Posting Information
We provide a scheduled posting end date to assist our candidates with their application planning. While this date reflects our latest plans, it is subject to change, and postings may be extended or removed earlier than expected.
We Take Care of Our Team
What You Drive at DTNA
Technical Leadership
- Provide architecture reviews and technical guidance for AI initiatives
- Offer feasibility insights and scalability considerations during AI intake discussions
- Identify high-impact AI and Data opportunities across business units and geographies
- Coordinate with DTG data leads, architects, and other group-wide technical leaders to develop and execute comprehensive data and AI technology solutions
- Collaborate with DTICI to create global data and AI architecture standards and solutions
- Support localization of applicable global data and AI solutions to meet regional needs and regulatory requirements
- Promote internal knowledge sharing through data and AI communities of practice
- Ensure the DTNA enterprise data platform remains AI-ready and scalable
- Direct collaboration with business leaders and directors — particularly within Aftermarket, Manufacturing and Finance domains — to better understand operational challenges, strategic priorities, and transformation goals
- Ensure platforms and data are AI-ready — architecting data foundations (including semantic/ontology layers, metadata, lineage, and access patterns) so that data is discoverable, well-governed, and consumable by AI and machine learning systems.
- Partner directly with the business to identify high-value use cases and translate them into functional proof-of-concepts (POCs) and minimum viable products (MVPs) for AI products, moving from concept to working prototype quickly
- Evaluate and pilot AI technology across the existing data stack and surrounding ecosystem — assessing tools, platforms, models, and vendors for fit, maturity, cost, and risk, and making recommendations that shape the architecture roadmap
- Champion an AI-first approach to data engineering and architecture — applying AI to accelerate data preparation, quality, documentation, and automation, and defaulting to AI-enabled solutions wherever they deliver measurable value
- Operationalize and scale AI solutions — establishing the patterns, pipelines, and MLOps/LLMOps practices needed to move validated POCs/MVPs into reliable, monitored production
- Embed responsible and governed AI practices — ensuring AI use aligns with data security, privacy, quality, and emerging AI governance standards throughout the lifecycle
- Advise and upskill stakeholders — serving as a technical-yet-business-fluent advisor who helps functional teams and leadership understand what is possible with AI and how to prioritize it
- Lead design and hands-on implementation of enterprise RAG and agent-based solutions
- Lead architecture and hands-on implementation of enterprise AI Agents leveraging Retrieval-Augmented Generation (RAG), Semantic retrieval, Vector Search, tool orchestration and Mult Agent workflows
- Define AI Quality metrics, evaluation frameworks, golden datasets, offline and online evaluation pipelines, LLM-as-judge workflows and regression testing to continuously improve AI Systems
- Design Semantic and ontology-driven data models that enable enterprise AI , self-service analytics, intelligent reasoning and knowledge discovery
- Evaluate and adopt emerging AI standards such as the Model Context Protocol (MCP) to enable secure, interoperable enterprise AI Agents and tool integration
- undefinedSupervisoryLead a team of AI and data professionals in driving innovation, operational efficiency, and strategic alignment across the enterpriseConduct employee reviews, Impact talks, and other employee feedback and guidanceLead employees in fostering their development plansRecruit, mentor, and retain top AI talentFoster a collaborative and inclusive team cultureDefine team goals and performance objectives aligned with strategic prioritiesBuild high performing engineering teams through strategic hiring , technical interviewing , mentoring and talent developmentProvide technical leadership through architecture reviews , design reviews , code reviews , AI Solution reviews and production readiness assessments
Knowledge You Should Bring
- Bachelor’s degree with focus in Technical or design field (Computer Science, Software Design, Data Science) from an accredited college/university and 7+ years of relevant experience, is required.
- Experience on major cloud analytics platforms
- Experience with major big data analytics platforms
- Experience with generative AI and major LLM models
- Experience deploying and managing large cloud compute workloads for optimal speed and cost efficiency
- Expert proficiency in SQLDeep, hands-on expertise in data modeling (conceptual, logical, physical) and both relational and non-relational stores
- Deep understanding of data engineering, data architecture
- Proven experience designing and operating ETL/ELT pipelines and modern data platforms (e.g., data warehouse, data lake, or lakehouse architectures)
- Demonstrated experience preparing and architecting data specifically for machine learning and AI consumption (feature readiness, quality, accessibility, governance)
- Demonstrated ability to handle structured and unstructured data at scale — ingestion, cleansing, profiling, validation, and aggregation
- Experience with streaming/real-time data architectures (e.g., Kafka, event-driven pipelines)
- Experience with distributed computing frameworks
- Experience with cloud-native AI services (Azure AI, AWS SageMaker)
- Experience with containerization and orchestration
- Hands-on work with agentic AI frameworks or orchestration tooling, and with major AI/data-platform ecosystems
- Experience productionizing and scaling AI solutions from prototype to reliable, monitored production
- Proven track record of delivering data and AI-driven business transformation
- Strong business acumen and ability to communicate complex technical concepts to non-technical stakeholders.
- Experience working in multinational or matrixed organizations
- An attached resume is required
Exceptional Candidates Might Have
- Advanced degree in Computer Science, AI, Data Science, or a related field
- Experience with large data sets and distributed computing a plus
- GitHub or similar collaborative development hub a plus
- Experience with Manufacturing, Finance, and Aftermarket data
- Familiarity with regulatory frameworks and data privacy laws across regions
- Multilingual capabilities or experience working across diverse cultural environments
- Thought leadership through publications and speaking engagements
Where We Work
This position is open to applicants who can work in (or relocate to) the following location(s)-
Portland, OR US. Relocation assistance is not available for this position.
Schedule Type:
Hybrid (4 days per week in-office / 1 day remote). This schedule builds our #OneTeamBestTeam culture, provides an unparalleled customer experience, and creates innovative solutions through in-person collaboration.
At Daimler Truck North America, we recognize our world is changing faster than ever before. By listening to the needs of today, we’re building to solve with cutting-edge solutions in sustainability and future driving technology across electric, hydrogen and autonomous. These solutions, backed by years of innovative success and achievement, continue DTNA’s legacy as the undisputed industry leader. Our evolving brand portfolio is second to none, including Freightliner Trucks, Western Star, Demand Detroit, Thomas Built Buses, Freightliner Custom Chassis, and Financial Services. Together, we work as one team towards our envisioned future – building a cleaner, safer and more efficient tomorrow for all.
That is what we are working toward - for all who keep the world moving.
Additional Information
Visa sponsorship will only be open to current Daimler Truck North America employees working under an existing U.S. Daimler Truck North America Visa
All other applicants must be legally authorized to work permanently in the country the position is located in at the time of application
Final candidate must successfully complete a criminal background check
Final candidate may be required to successfully complete a pre-employment drug screen
Contractors, professional services, or other contingent workers should confirm with their local agency if they are eligible to apply for FTE positions
EEO - Disabled/Veterans
Daimler Truck North America is committed to workforce inclusion and providing an environment where equal employment opportunities are available to all applicants and employees without regard to race, color, sex (including pregnancy), religion, national origin, age, marital status, family relationship, disability, sexual orientation, gender identity and expression (including transgender and transitioning status), genetic information, or veteran status.
For an accommodation or special assistance with applying for a posted position, please contact our Human Resources department at 503-745-8982 or toll free 800-206-3369. For TTY/TDD enabled call 503-745-2137 or toll free 866-355-6935.
