Senior Data & AI Engineer

Inside the Role

This is a senior individual contributor role focused on building, proving out, and enabling artificial intelligence, machine learning (ML), and automation solutions across DTNA. The person in this role is a hands-on builder who delivers by building alongside the business teams to enable others and ensure sustainability. We are seeking an experienced and innovative data and AI engineer to join our Business Data Analytics Team (BDAT) and help cultivate, accelerate, and activate a data- and AI-driven culture at DTNA. You will play a pivotal role in shaping how the organization applies data, analytics, automation, and AI, developing new ways of working and sharing those best practices across the company. You will be taking promising prototypes to governed, production-ready solutions, working hands-on with information technology (IT) and platform teams, coaching teams to build their own solutions, and serving as a technical reference for BDAT and across DTNA. Your technical expertise will be instrumental in driving data and AI-informed decision-making across all levels of the organization. Just as importantly, you are a willing teacher and collaborator who builds trust, connects people, and inspires action across all levels of the organization. We invite you to help us build the future of data and AI at DTNA and support our vision of making data and AI a common language across the organization.

CI Department Culture

The Continuous Improvement department fosters a culture of open-mindedness, adaptability, and collaboration. We believe in continuously evolving for the better, embracing change, and working together to achieve shared goals. Team members are encouraged to bring their unique perspectives, collaborate across initiatives, and maintain an inclusive environment where all voices are heard, respected, and valued.

The Business Data Analytics Team (BDAT) within the Continuous Improvement (CI) department serves as the enterprise's Center of Enablement for self-service data, analytics, automation, and AI, cultivating a data-driven, continuous improvement culture across Daimler Truck North America (DTNA) and empowering business units to make informed decisions through scalable, sustainable, and democratized data practices.

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

Position offers a starting salary range of $117,000  - $150,000 USD

Pay offered dependent on knowledge, skills, and experience​

Benefits include annual bonus program; 401k company contribution with company match up to 6% as well as 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 and volunteer paid time off; short-term and long-term disability plans.

What You Drive at DTNA

Technical Depth & Solution Delivery

• Design, build, and deploy AI/ML, agentic, and automation solutions for high-impact, high-complexity business initiatives, co-developing with business teams so they can own, enhance, and sustain what is built, and translating business objectives into working solutions and rapid proofs of concept.

• Take promising prototypes to governed, production-ready solutions in partnership with IT, the Data Intelligence Hub (DIH), and business-embedded data teams, applying sound engineering practices such as continuous integration and delivery pipelines, automated testing, and documentation.

• Build reusable solution patterns, such as connecting business data to conversational AI tools, so that a solution proven once can be adopted by many teams.

• Develop new ways of working with data, analytics, automation, and AI, and share the resulting best practices with teams across DTNA.

• Support CI colleagues in developing data, analytics, automation, and AI solutions for their CI programs, advancing CI culture and adoption across DTNA.

• Serve as a technical reference for BDAT and across DTNA on AI engineering, data platforms, and best practices.

Technical Enablement

• Partner with IT and the DIH to evaluate, pilot, and integrate the tools and platforms that enable self-service analytics, automation, and AI (e.g., Snowflake and Snowflake Cortex, Microsoft Copilot and Copilot Studio, LibreChat, Power Platform, GitHub).

• Work hands-on with IT and platform teams on the technical details of making these tools work together, including data connections and APIs, access and governance, usage and cost transparency, and auditing of self-service environments.

• Stay current on emerging data and AI trends, including GenAI, agentic approaches, and automation, test them hands-on, and recommend what DTNA should adopt and when.

Coaching & Upskilling

• Lead hands-on coaching and co-development engagements across business units, from hands-on-keyboard co-development to coaching teams through their own problem solving, using a "teach others to build" approach with tangible deliverables.

• Coach teams to apply data, analytics, automation, and AI in their own CI work.

• Provide technical consultation and innovative approaches to solve unique business challenges with data, analytics, automation, and AI.

• Mentor and develop junior team members and data community practitioners.

Strategy & Advisory

• Collaborate with senior leadership, IT, the AI Center of Excellence (AI CoE), and the enterprise data community (the Hub for Analytic Collaboration) to advance a data- and AI-driven culture and promote self-service analytics, automation, and AI.

• Act as a strategic and technical advisor to business units on the art of the possible, recommending the right approach (AI/ML, automation, analytics, or BI) for each use case, including when a simpler solution is the better one.

• Identify new opportunities to apply data, analytics, and AI to strategic initiatives, and challenge established ways of working where the technology points to a better approach.

Data & AI Community Building

• Foster and grow an engaged data and AI community built on collaboration, knowledge sharing, and best practices.

• Participate in community events, including the annual DT Week conference, workshops, and hackathons, connecting practitioners across all levels and departments.

Knowledge You Should Bring

• Bachelor's degree and 5+ years of relevant experience, or 8 years of relevant experience in lieu of a degree

• Advanced proficiency in Python and SQL, with the ability to write, review, test, and productionize code, and to sanity-check AI-generated output

• 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 (e.g., Snowflake Cortex, Microsoft Copilot Studio, LibreChat, or comparable platforms), with sound judgment on when each is and is not appropriate, and a habit of continuous learning as the technology changes

• Strong grounding in machine learning and statistical methods

• Hands-on experience with cloud data platforms (e.g., Snowflake), including data modeling, extraction, transformation, and loading (ETL), and API integrations

• Working knowledge of DevOps practices, including version control (e.g., GitHub), automated testing, and continuous integration and delivery pipelines

• Ability to coach and co-develop with teams at all levels of the organization, and to translate between business and technical audiences, including executives

Exceptional Candidates Might Have

• Degree in Business, Mathematics, Computer Science, Statistics, Analytics, or a re