Senior Engineer, Human Machine Teaming (R5648)

What you'll do:

• Plan and conduct field research using ethnographic methods, observation, knowledge elicitation, and cognitive task analysis with the customer, operators, and pilots.
• Conduct front-end human factors analyses to decompose the collaborative work that characterizes real operations.
• Produce mission threads, baseline use cases, and context-sensitive variants of baselines that drive design and experimentation.
• Support translation of operator needs into collaborative work requirement profiles in concert with other HMT staff.
• Support operational and readiness assessment exercises with fielded systems, including field testing under real tempo, degraded communications, and off-nominal events.
• Provide embedded HMT support within major product lines, aligned to Shield AI’s HMT strategy.
• Support HMT after-action review and debrief procedures, and feed lessons learned back into requirements profiles, risk assessments, HMI design, and training.
• Manage operator and SME engagement end to end, from scheduling and consent through data handling and participant feedback.
• Contribute to adoption playbooks and training content, and prepare trip reports and briefings containing product recommendations.
• Travel to company, test, demonstration, and customer locations to conduct project work (approximately 40%).

Required qualifications:

Engineer II: typically requires a minimum of 2 years of related experience with a Bachelor's degree; or 0 years and a Master's degree; or a PhD without experience. Senior Engineer: typically requires a minimum of 3–5 years of related experience with a Bachelor's degree; or 2–4 years and a Master's degree; or 2 years with a PhD; or equivalent work experience.
A degree in human factors engineering or psychology, cognitive systems engineering, applied cognitive science, industrial and systems engineering, or a related field, or equivalent operational experience.
Demonstrated ability to plan and execute field studies or operational assessments with human participants, and report findings to engineering and operator/customer audiences.
Working knowledge of human machine teaming, human factors, human performance, and training theory and measurement, including cognitive task analysis, knowledge elicitation, and needs analysis.
Comfort working in operational environments such as flight lines, ranges, exercises, and customer sites, gathering good data without disrupting the mission.
Experience in multidisciplinary settings, and ability to work in complex, ambiguous problem spaces and produce clear and structured artifacts.
Strong teamwork and collaboration skills, and written and verbal communication skills.

Preferred qualifications:

Operational background as aircrew, UAV operator, mission commander, or in intelligence or C2/battle management.
Hands-on experience with human machine teaming, MUM-T, human-robot interaction, or applied artificial intelligence, specifically in mission autonomy applications such as UAV Groups 1–5.
Experience with mission planning, C2, battle management, and UAV or pilot training concepts, processes, and doctrine, and with ground control stations or HMIs.
Experience in scenario design, and with modeling and simulation tools and methods.
Experience conducting operational or training exercises in immersive simulation environments, and with and with developmental or operational test and evaluation, or readiness assessments with fielded systems.
Experience conducting after-action reviews, and generating lessons-learned or plans of action and milestones in a customer-facing or forward-deployed role.
Experience with designing or delivering UAV operator or pilot crew operational training.
Familiarity with traceability methods, or with AI assurance frameworks.
Willingness to use agentic AI to speed the path from design concept to fielded product.
U.S. DoD Secret clearance eligible, with the ability to obtain and maintain Top Secret, SCI, and/or SAP-level access. U.S. citizenship required.