Autonomous Vehicle Technology Manager

We're Hiring: Autonomous Vehicle Technology Manager
Location: United Arab Emirates (Remote)
Employment Type: Full-Time
Experience Level: Mid-Level to Senior
Work Arrangement: Fully Remote
About Us
We are a globally focused organization committed to developing and deploying advanced mobility technologies that improve transportation safety, efficiency, reliability, and operational performance across diverse environments.
Our teams collaborate across Autonomous Systems, Robotics, Software, AI, Computer Vision, Vehicle Engineering, Mapping, Fleet Operations, Safety, Cybersecurity, Product, and external technology partners to develop scalable autonomous vehicle solutions.
The Role
We are seeking an experienced Autonomous Vehicle Technology Manager to lead the strategy, development, integration, testing, deployment, and continuous improvement of autonomous vehicle technologies and intelligent mobility systems.
The ideal candidate will manage multidisciplinary programs spanning autonomous driving software, perception, localization, planning, control, vehicle platforms, sensors, simulation, mapping, connectivity, fleet operations, safety, and technology validation.
Key Responsibilities
Develop and implement autonomous vehicle technology strategies aligned with organizational objectives and mobility requirements.
Define technology roadmaps covering autonomous driving capabilities, vehicle platforms, sensors, software, AI, infrastructure, and supporting systems.
Lead autonomous vehicle technology programs from concept and feasibility through development, testing, deployment, and operational optimization.
Evaluate autonomous-driving technologies, platforms, software architectures, sensors, compute systems, and technology providers.
Coordinate multidisciplinary teams across software, AI, robotics, vehicle engineering, electrical systems, safety, cybersecurity, mapping, operations, and product management.
Define functional, technical, operational, and performance requirements for autonomous vehicle systems.
Oversee development and integration of autonomous driving technology across vehicle platforms.
Manage perception systems using cameras, LiDAR, radar, ultrasonic sensors, and other sensing technologies.
Oversee localization and positioning technologies including GNSS, inertial systems, SLAM, HD maps, and sensor fusion.
Coordinate motion planning, path planning, behavior planning, decision-making, and vehicle-control technologies.
Support development and integration of machine-learning and AI models for autonomous driving applications.
Oversee sensor fusion, object detection, tracking, classification, free-space detection, and environmental understanding.
Coordinate vehicle interface, actuation, drive-by-wire, steering, braking, and propulsion integration.
Establish system architectures and interfaces between autonomous driving software and vehicle hardware.
Manage integration with fleet-management, telematics, connectivity, cloud, and operational platforms.
Establish development, simulation, testing, validation, and release processes for autonomous vehicle technologies.
Coordinate software-in-the-loop, hardware-in-the-loop, vehicle-in-the-loop, simulation, closed-course, and public-road testing where applicable.
Develop test strategies covering normal, edge-case, degraded, and failure scenarios.
Define technology validation criteria, acceptance thresholds, performance metrics, and release gates.
Monitor autonomous-system performance across perception, localization, planning, control, and overall driving behavior.
Analyze disengagements, intervention events, safety incidents, near misses, system failures, and operational anomalies.
Lead root-cause analysis and corrective actions for autonomous-system performance issues.
Establish processes for collecting, labeling, managing, and analyzing vehicle sensor and operational data.
Coordinate data pipelines for training, validation, regression testing, and system improvement.
Support simulation environments and scenario libraries for large-scale autonomous-system testing.
Develop and maintain scenario coverage for traffic, weather, road geometry, pedestrians, cyclists, vehicles, obstacles, and other operating conditions.
Establish performance benchmarks for autonomous-driving systems and technology releases.
Monitor fleet-level performance and identify recurring system limitations and improvement opportunities.
Coordinate mapping, localization, route-planning, and geofencing requirements for operational deployment areas.
Support definition of operational design domains and system operating limitations.
Ensure autonomous systems operate within approved environmental, geographic, weather, speed, and operational constraints.
Coordinate technology deployment, commissioning, configuration, software releases, and fleet updates.
Establish rollback, recovery, degraded-mode, and contingency procedures for software and autonomous-system failures.
Work closely with Vehicle Engineering and Maintenance teams to address hardware reliability and integration issues.
Coordinate sensor calibration, health monitoring, diagnostics, and preventive-maintenance requirements.
Support autonomous fleet readiness assessments before operational deployment.
Establish technology monitoring and incident-response processes for deployed autonomous vehicles.
Coordinate with Safety and Risk teams on hazard analysis, safety cases, risk controls, and operational safety requirements.
Support compliance with applicable autonomous-vehicle, transportation, functional-safety, cybersecurity, and data-protection requirements.
Coordinate cybersecurity controls for vehicle networks, ECUs, sensors, communications, cloud systems, and remote-access platforms.
Support secure software development, authentication, access control, encryption, vulnerability management, and software-update processes.
Manage autonomous-technology vendors, OEMs, system integrators, software providers, mapping companies, sensor suppliers, and research partners.
Define technical requirements, service levels, integration responsibilities, acceptance criteria, and performance expectations for technology partners.
Monitor vendor performance, technology maturity, delivery quality, support responsiveness, and system reliability.
Manage technology budgets, project costs, resources, schedules, and implementation risks.
Evaluate technology investments through performance, scalability, reliability, safety, total cost of ownership, and business-value analysis.
Identify emerging technologies including advanced AI, foundation models, computer vision, edge computing, V2X, digital twins, simulation, and next-generation sensing.
Conduct technology assessments, proof-of-concept programs, pilots, and controlled trials.
Support partnerships with universities, research institutions, technology companies, mobility providers, and industry organizations.
Develop technical documentation covering system architecture, requirements, testing, deployment, operations, maintenance, and troubleshooting.
Establish technology governance covering architecture, configuration management, software versions, data, interfaces, and lifecycle management.
Provide management with regular reports covering autonomous-system performance, safety, reliability, technology development, costs, risks, and improvement opportunities.
Key Performance Indicators
Autonomous system availability
Autonomous fleet uptime
Autonomous driving miles or kilometers
Autonomous operation rate
Human intervention rate
Disengagement frequency
Safety-critical event rate
Collision and incident rate
Near-miss frequency
Perception accuracy
Object-detection performance
False-positive and false-negative rates
Localization accuracy
Planning performance
Trajectory and path-following accuracy
Control-system performance
Route completion rate
Autonomous mission completion rate
Operational design domain compliance
System failure rate
Mean time between failures
Mean time to recovery
Software release quality
Regression-test pass rate
Simulation scenario coverage
Test coverage
Validation completion
Defect discovery and closure rate
Sensor availability
Sensor calibration accuracy
Vehicle diagnostic performance
Mapping accuracy and coverage
Fleet software-update success rate
Data quality and availability
AI model performance
Technology deployment schedule adherence
Project budget performance
Vendor SLA compliance
System scalability
Cybersecurity compliance
Technology lifecycle cost
Autonomous fleet operating cost
Continuous-improvement performance
Ideal Candidate
The successful candidate should have strong experience in autonomous vehicles, autonomous driving, robotics, intelligent transportation systems, ADAS, mobile robotics, AI, computer vision, vehicle technology, or related advanced mobility environments, preferably within automotive, logistics, transportation, robotics, technology, or large-scale mobility operations.
The candidate should demonstrate:
Strong understanding of autonomous vehicle technology and sy

Work arrangement
No