Senior Engineer, Human Machine Teaming (R5648)

About the Role

The Human Machine Teaming (HMT) Group at Shield AI is hiring an Engineer II or Senior Engineer to join our HMT Operations capability. HMT refers to the design, management, and assurance of the adaptive relationships between operators and Hivemind-enabled mission autonomy—not just an interface problem or a function-allocation exercise. This role keeps HMT research and development grounded in real-world operations with actual operators under real tempo. You will work alongside the HMT Operations Lead, conducting field research with Shield AI pilots, operators, and customer or external subject matter experts (SMEs). Your findings will translate into updates for collaborative work requirement profiles used by design and experimentation teams, while embedding HMT expertise into product lines and field operations.

Responsibilities

• Plan and conduct field research using ethnographic methods, observation, knowledge elicitation, and cognitive task analysis with customers, 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 to 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 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, feeding lessons learned 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 with product recommendations.
• Travel to company, test, demonstration, and customer locations to conduct project work (approximately 40%).

Requirements

• Engineer II: Typically requires a minimum of 2 years of related experience with a Bachelor’s degree; or 0 years with 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 with a Master’s degree; or 2 years with a PhD; or equivalent work experience.
• A degree in human factors engineering, 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 while gathering data without disrupting the mission.
• Experience in multidisciplinary settings, with the ability to work in complex, ambiguous problem spaces and produce clear, structured artifacts.
• Strong teamwork, collaboration, and written/verbal communication skills.
• U.S. citizenship required; eligibility for U.S. DoD Secret clearance, with the ability to obtain and maintain Top Secret, SCI, and/or SAP-level access.

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 (e.g., UAV Groups 1–5).
• Experience with mission planning, C2, battle management, 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, 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 customer-facing or forward-deployed roles.
• Experience designing or delivering UAV operator or pilot crew operational training.
• Familiarity with traceability methods or AI assurance frameworks.
• Willingness to use agentic AI to accelerate the path from design concept to fielded product.