Founding Technical Lead – Autonomous Systems for Rural Emergency Healthcare

Location: Remote within the United States, with periodic work in Virginia’s Shenandoah Valley
Potential future role: Full-time technical leadership, contingent upon project selection and funding

The opportunity

Priority Patient Transport is assembling a team to pursue an ambitious National Science Foundation X-Labs mission: making lifesaving emergency capabilities available to rural patients before a conventional ambulance can arrive.

Our vision is an autonomous physical-AI platform that can select, configure, and deliver intelligent medical payloads to patients in rural and underserved areas. The platform may incorporate uncrewed aircraft, autonomous ground vehicles, modular emergency-care payloads, edge AI, degraded-connectivity operation, human-machine interaction, and integration with emergency medical services.

We are seeking an entrepreneurial technical leader who can help transform this mission into a technically credible research and development program—and potentially lead that program through prototype development, real-world validation, and national expansion.

Why Priority Patient Transport

Priority Patient Transport brings approximately 20 years of experience providing Critical Care, Advanced Life Support, and Basic Life Support ambulance services throughout Virginia’s Shenandoah Valley.

Our teams understand rural emergency healthcare as an operational reality, not an abstract research problem. We have transported and cared for patients across long distances, difficult terrain, isolated communities, and severe weather conditions. Our paramedics, EMTs, dispatch personnel, and operational leaders possess detailed knowledge of what happens from the initial request for service through patient assessment, treatment, transport, and arrival at the receiving facility.

Priority can contribute resources rarely available to an early-stage autonomous-systems program:

• Approximately two decades of rural ambulance and medical-transport experience.

• Practicing paramedics and EMTs who can help define requirements, failure modes, workflows, and realistic emergency scenarios.

• Historical operational information that may reveal response patterns, travel times, routes, geographic barriers, weather-related constraints, and locations where earlier delivery of emergency capabilities could have the greatest value.

• Knowledge of rural roads, hospitals, communities, communications limitations, and emergency-response conditions throughout the Shenandoah Valley.

• Ambulances, clinical equipment, training resources, and experienced personnel capable of supporting controlled development and evaluation.

• The ability to integrate autonomous-delivery trials alongside conventional ambulance operations under appropriate safety, privacy, regulatory, and clinical controls.

This creates an opportunity to develop the technology through progressively realistic operations rather than relying exclusively on isolated laboratory demonstrations or artificial test environments.

Early autonomous missions could operate in parallel with actual ambulance responses without replacing, delaying, or interfering with conventional care. For example, an autonomous vehicle could be dispatched alongside an ambulance carrying a non-clinical or simulated payload. Its route, arrival time, communications performance, delivery accuracy, and response to weather and terrain could then be compared with the real crew’s experience.

As safety and capability are demonstrated, testing could progress from simulated payloads to training equipment, supervised medical supplies, and eventually appropriately authorized emergency-care applications. This approach would generate evidence about whether the technology works under the conditions that matter: real distances, real roads, real weather, real communications limitations, and real emergency-response timelines.

Any operational or patient-related information used for research would be subject to appropriate privacy protections, permissions, data-use controls, de-identification, and regulatory review. We do not assume that every historical record is immediately research-ready. We believe our operational history provides an unusually valuable foundation for identifying the right questions, constructing representative datasets, and validating solutions in the environments they are intended to serve.

The technical mission

The project is broader than delivering a conventional medical kit by drone.

We envision a vehicle-independent autonomous platform capable of determining what emergency capability is needed, selecting or configuring the appropriate payload, choosing the appropriate delivery system, reaching the patient, and coordinating with patients, bystanders, clinicians, dispatch centers, and responding EMS crews.

Potential research and development areas include:

• Autonomous selection and configuration of medical payloads based on incident information.

• Vehicle-independent autonomy for aerial and ground delivery systems.

• Safe navigation in mountainous, wooded, agricultural, residential, and connectivity-limited environments.

• Last-100-meter localization and delivery.

• Edge AI and continued operation without reliable cloud connectivity or GPS.

• Intelligent medical payloads capable of guiding users and verifying correct application.

• Coordination among autonomous systems, 911 centers, EMS units, hospitals, clinicians, patients, and bystanders.

• Simulation-to-real training using representative rural emergency scenarios.

• Safety-bounded autonomy for high-consequence healthcare applications.

• Modular architecture that allows outside organizations to develop compatible vehicles, payloads, sensors, and emergency-care capabilities.

The initial platform may use an uncrewed aircraft to deliver a modular “Golden Box” containing emergency equipment. The broader mission, however, is to create a new technological foundation for autonomous rural emergency response—not a single drone or delivery product.

What you would do

During the initial engagement, you would work directly with company leadership and prospective research partners to:

• Define the technical architecture for an autonomous rural emergency-response platform.

• Identify what must be invented beyond existing drone-delivery, telemedicine, and medical-device technologies.

• Design the interaction among autonomous vehicles, medical payloads, dispatch intelligence, communications, patients, bystanders, clinicians, and EMS personnel.

• Translate rural EMS experience and operational data into technical requirements, simulations, experiments, and performance benchmarks.

• Develop a phased prototype, testing, safety, and validation strategy.

• Establish an approach for simulation, controlled testing, shadow deployment, and progressively advanced operational demonstrations.

• Identify critical reliability, cybersecurity, human-factors, regulatory, privacy, and systems-engineering requirements.

• Help recruit universities, robotics researchers, medical-device experts, aviation partners, health systems, and other technical collaborators.

• Contribute substantially to the technical sections of an NSF X-Labs proposal.

• Develop meaningful technical milestones, staffing requirements, facilities, equipment needs, and budgets.

• Present and defend the mission during partner discussions and, if invited, the NSF oral-review process.

If the project advances, this individual could become the full-time technical leader of the proposed X-Lab and direct a multidisciplinary team through prototype development, rural field validation, and expansion into additional regions.

Our proposed development approach

We anticipate a progressive development model designed to protect patients while generating increasingly realistic evidence.

Simulation and architecture

Develop the system architecture, rural emergency simulations, representative scenarios, payload requirements, safety controls, and measurable performance standards.

Controlled testing

Evaluate autonomous vehicles and payloads using closed courses, simulated patients, training equipment, and controlled rural environments.

Shadow deployment

Dispatch an autonomous system in parallel with—not in place of—a staffed ambulance. The autonomous system would initially carry a simulated or non-clinical payload, allowing the team to compare:

• Dispatch and arrival times.

• Air or ground routes.

• Communications performance.

• Delivery accuracy.

• Weather and terrain limitations.

• System reliability.

• Interaction with EMS operations.

• The potential time advantage for delivering specific emergency capabilities.

Patient care would continue to depend on the conventional EMS response during this stage.

Supervised operational demonstrations

As safety and technical performance are established, demonstrations could progress to supervised delivery of training equipment, non-critical supplies, and appropriately authorized medical payloads.

Authorized emergency-care applications

The long-term objective is a validated platform capable of safely delivering and supporting meaningful emergency interventions before conventional responders arrive.

Who we are looking for

The strongest candidate will combine technical depth with founder-level initiative.

You should be comfortable moving from an ambitious mission to a defensible technical architecture, building a team around unanswered questions, and communicating with both researchers and operational EMS professionals.

Relevant backgrounds may include:

• Robotics, autonomous vehicles, uncrewed aircraft systems, or cyber-physical systems.

• Embodied AI, edge AI, distributed autonomy, sensor fusion, planning, or control systems.

• Safety-critical systems engineering.

• Medical robotics, medical devices, digital-health hardware, or prehospital technology.

• Human-robot interaction or human factors.

• Simulation-to-real learning and field robotics.

• Aerospace, defense, disaster response, logistics, or emergency technology.

• Leadership of multidisciplinary R&D programs, startups, research laboratories, or advanced-prototype teams.

We do not expect one person to be the expert in every field. We do expect the technical lead to recognize what expertise is missing and build a team capable of addressing it.

Attributes that matter

• Entrepreneurial and comfortable beginning with an unsolved problem.

• Able to distinguish foundational platform research from ordinary product integration.

• Willing to challenge assumptions while remaining focused on the mission.

• Skilled at converting operational needs into testable engineering requirements.

• Credible with researchers, engineers, clinicians, government reviewers, and commercial partners.

• Comfortable working under milestone-based funding and technical uncertainty.

• Motivated by the opportunity to transform access to emergency care in rural communities.

• Prepared to consider a full-time leadership commitment if the project progresses.

Helpful but not required

• Advanced degree in a relevant technical discipline.

• Prior experience as a principal investigator, technical director, chief engineer, startup founder, or CTO.

• Experience writing or leading major federal research proposals.

• Experience with NSF, DARPA, ARPA-H, other-transaction agreements, or milestone-based R&D programs.

• Familiarity with regulatory pathways for advanced uncrewed-aircraft operations.

• Experience with regulated medical technology, clinical research, or emergency medicine.

• Experience moving technology from early research through field demonstration.

• Experience recruiting and leading multidisciplinary technical teams.

About the initial engagement

The immediate work will focus on technical concept development, partnership formation, and preparation of an NSF X-Labs proposal. Selection or funding by NSF is not guaranteed.

The person chosen for this role may be proposed as senior/key personnel only after mutual agreement regarding the role, availability, required disclosures, and future commitment. The NSF program generally expects senior/key leadership to be dedicated full-time by the beginning of Phase 1 unless NSF approves otherwise.