Staff Production Engineering Specialist (R6041) en Shieldai

Shield AI is seeking a highly capable Production Engineering Technician to oversee technician training, continuous improvement initiatives, and production analytics for the V-BAT production line. The role is responsible for developing workforce capability and establishing robust, data‑driven operational systems that enhance safety, quality, delivery performance, cost efficiency, and production scalability.

Training

Own the VBAT production training program, including onboarding, role-based training, cross-training, recertification, ongoing skills development, and technician qualification records.

Develop and deliver effective classroom, workstation, and on-the-job training for assembly, production, and test processes; maintain skills matrices, on the job training assessments, and training readiness metrics.

Continuously identify skill gaps, align training to current production needs, and assess effectiveness through observations, competency checks, audit results, technician feedback, and production performance.

Lean Manufacturing and Continuous Improvement

Lead continuous-improvement initiatives using lean manufacturing principles—including 5S, visual management, standard work, root-cause analysis, waste reduction, and flow optimization—to improve safety, quality, delivery, and cost.

Use production, quality, and training data to identify and help resolve bottlenecks, cycle-time variation, recurring defects, rework, material-flow issues, equipment downtime, ergonomic risks, and workforce capability gaps.

Own the CCAR process and lead the Manufacturing Council, creating a responsive closed-loop system that turns technician feedback and shop-floor opportunities into prioritized, implemented, verified, and sustained improvements.

Data Analytics

Build a data-driven operating model for the VBAT production team by establishing standardized performance metrics, reporting cadences, and visual management routines that enable timely, data-driven decisions.

Develop and maintain daily, weekly, and monthly dashboards tracking output versus plan, throughput, first-pass yield, defects and rework, cycle time, downtime, labor efficiency, training completion, and cross-training coverage.

Analyze production capacity, staffing, and improvement impact using takt time, labor content, workstation capacity, skills readiness, and before-and-after performance data to support production-ramp planning and sustain measurable gains.

Bachelors degree in Industrial or Systems Engineer, or Data Analytics; equivalent technical experience in avionics or aerospace production will be considered.   

3+ years of experience in a manufacturing or technical support role, preferably within aerospace, defense, UAS, or other complex hardware manufacturing environments.

Ability to operate effectively in a fast-paced, highly dynamic environment with evolving priorities.   

Excellent analytical, organizational, and communication skills.   

U.S. citizenship and ability to obtain/maintain a security clearance.

Experience with data visualization tools, such as Power BI, Palantir, Tableau, Cognos, and/or Microsoft Access.

Proficiency in Lean Manufacturing principles, including 5S, visual management, standard work, root‑cause analysis, waste reduction, and flow optimization.

Ability to translate technician feedback and production challenges into structured problem-solving activities.

Experience operating, maintaining, and facilitating training programs and performance across large scale operations and organizations.

Excellent communication and presentation skills, with the ability to train and influence technicians, supervisors, and cross-functional stakeholders.

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Full-time regular employee offer package:

Pay within range listed + Bonus + Benefits + Equity

 

Temporary employee offer package:

Pay within range listed above + temporary benefits package (applicable after 60 days of employment)

 

Salary compensation is influenced by a wide array of factors including but not limited to skill set, level of experience, licenses and certifications, and specific work location. All offers are contingent on a cleared background and possible reference check. Military fellows and part-time employees are not eligible for benefits. Please speak to your talent acquisition representative for more information.

 

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Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status. If you have a disability or special need that requires accommodation, please let us know.