Job SummaryThis role supports AI development and server rack deployment lifecycle activities, spanning presales design through postdeployment operations. The focus is on building and maintaining data pipelines, models, and automation that enable AI solutions, racklevel configurations, demand planning, deployment tracking, and postship optimization.
This role bridges AI initiatives with physical infrastructure execution.
This is a backfill role with expanded scope and a modernized title aligned to AIdriven infrastructure delivery.
Role Description
- Build and maintain data pipelines that support AI development, analytics, and automation across server and rack deployments
- Enable presales activities by supporting data models for solution design, BOM creation, capacity planning, and scenario analysis
- Support AI initiatives by preparing and curating data for machine learning, GenAI, and decisionsupport use cases
- Partner with presales, solutions engineering, IDCS, and operations teams to ensure data continuity from design through deployment and postship support
- Integrate data across enterprise systems including configuration tools, inventory systems, manufacturing data, logistics, and deployment tracking
- Develop dashboards and analysis that track deployment progress, risks, SLAs, and operational performance
- Ensure data quality, reliability, and traceability across the full lifecycle of AI and infrastructure projects
- Document standards, repeatable data patterns, and automation to scale AIenabled infrastructure delivery
Behaviors and Competencies
Communication: Can lead and model exceptional communication at all levels of the organization, develop and implement communication strategies, and coach others to improve their communication skills
Adaptability: Can drive strategic transformations, inspire others to embrace change, and foster a culture of continuous adaptation
Collaboration: Can lead complex team projects, inspire others to collaborate effectively, and foster a culture of mutual respect and shared purpose
Time-Management:
Problem Solving: Can lead strategic problem-solving initiatives, inspire others to improve their problem-solving skills, and foster a culture of proactive problem-solving
Initiative: Can lead strategic and complex initiatives, inspire others to take initiative, and foster a culture of continuous improvement
Analytical Thinking: Can lead and innovate in the application of analytical thinking, solve complex problems, influence others, and contribute to best practices.
Skill Level Requirements
Strong experience in data engineering fundamentals, including ETL/ELT pipelines, data modeling, and cloudbased data platforms
Handson experience supporting AI or analytics initiatives through data preparation and orchestration
Proficiency in Python and SQL
Experience working with structured and semistructured data across operational and engineering systems
Ability to translate presales and operational needs into scalable data solutions
Preferred ExperienceExperience supporting AI workloads tied to infrastructure, manufacturing, or data center environments
Familiarity with GenAI, LLMadjacent workflows, or analytics supporting deployment automation
Exposure to server, rack, or data center lifecycle data, from design through delivery and postdeployment
Experience working in presales, services, or solution delivery organizations
Other Requirements
The estimated annual pay range for this position is $120,000 - $145,000 which includes a base salary and bonus. The compensation for this position is dependent on job-related knowledge, skills, experience, and market location and, therefore, will vary from individual to individual. Benefits may include, but are not limited to, medical, vision, dental, 401K, and flexible spending.
