LandOffer
Staff Engineer, Data Platform (R5659)
Job details
- Work mode
- On-site
- Employment
- Full-time
- Level
- Staff / principal
- Posted
- Aug 26, 2026
- Last confirmed open
- Oct 24, 2026
What you'll need to apply
Fields this application requires
Company-specific questions
- Shield AI provides technology, services, and support to the United States military and allied forces with their various missions. If selected for employment with Shield AI, your contributions will directly relate to and/or support these missions. Are there any reasons why you would not be able to fully contribute in support of the U.S. military and allied forces?
- Please state your full legal name:
- Are you a transitioning service member?
- What full time job(s) are you applying for?essay
About this role
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide.
For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description
We are looking for a Staff Data Platform Engineer to help define and build the data foundation of the AI Factory. The Data Platform provides a unifying, knowledge-graph-centered API layer for human and agentic workflows. It connects configurations, requirements, software versions, test executions, files, signals, training data, and results through stable identities and typed relationships.
It also provides consistent access to the storage and compute systems behind those data products. This is a hands-on technical leadership role. You will design platform architecture, implement production software, evaluate storage and compute technologies, establish data-modeling patterns, and work directly with teams collecting and consuming mission-critical data.
Success requires balancing developer productivity, semantic clarity, operational reliability, system performance, portability, and long-term maintainability.