Embedded Engineering Manager - Robotics & Drones

Aptiv is building a new Robotics business focused on Autonomous Mobile Robots (AMRs) and Drones for warehouse, industrial, and adjacent markets. We are seeking an Embedded Engineering Manager to lead teams responsible for the development of robotics and drone hardware and software systems. In this role, you will define and execute technology and product roadmaps spanning embedded systems, software platforms, autonomy, and machine learning-based perception, while building and leading high-performing engineering teams. You will balance strong technical leadership with people management, driving the delivery of reliable, scalable, and production-ready robotics and drone solutions. Working closely with autonomy, localization, safety, hardware, data, and product teams, you will ensure system capabilities meet performance, safety, and commercial objectives.

Responsibilities

• Own and drive the technical strategy, architecture, and execution for embedded systems and software across AMR and drone platforms.
• Provide technical leadership across sensing, compute platforms, data pipelines, perception algorithms, embedded software, and system integration.
• Collaborate with Product Managers and Technical Program Managers to shape product roadmaps, ensuring technical feasibility, realistic resource planning, and alignment with business objectives.
• Develop and maintain technology and competency roadmaps by monitoring industry trends, emerging technologies, and future product requirements.
• Serve as a technical thought leader for systems engineering, embedded software, robotics, autonomy, and perception technologies.
• Guide key technical trade-offs involving performance, latency, reliability, safety, compute resources, scalability, maintainability, and cost.
• Lead engineering teams responsible for:
• Embedded systems architecture and platform software.
• Sensor integration and data acquisition (cameras, lidar, radar, depth sensors, IMUs, and related technologies).
• Sensor data ingestion, preprocessing, synchronization, and transport.
• Runtime inference, diagnostics, monitoring, and health management.
• System-level integration across perception, localization, planning, safety, and control subsystems.
• Establish engineering standards, architecture guidelines, and software development best practices that support scalable, production-ready robotics systems.
• Drive technical execution from concept through deployment while ensuring reuse across multiple robot and autonomous platform form factors.
• Resolve critical technical escalations and remove engineering roadblocks by working directly with product teams when necessary.
• Support product development teams throughout the development lifecycle, ensuring technical risks are identified and mitigated early.
• Drive cross-functional problem solving across hardware, software, autonomy, safety, and product organizations.
• Partner with Technical Program Managers and engineering leads to balance priorities, schedules, resources, and technical scope.
• Drive continuous process, methodology, and workflow improvements to improve engineering quality, predictability, and efficiency.
• Directly manage and grow multiple systems, software, and perception engineering teams.
• Establish clear goals, expectations, priorities, and performance objectives aligned with product and organizational strategies.
• Lead hiring, onboarding, performance management, succession planning, and career development activities.
• Mentor engineers and technical leaders in:
• Systems architecture and embedded software design.
• Robotics and autonomous system development.
• Scalable software engineering and DevOps practices.
• Root-cause analysis, problem solving, and technical decision making.
• Foster a culture of ownership, quality, innovation, collaboration, and continuous learning.
• Identify future staffing, skillset, and resource needs based on product roadmaps and organizational growth plans.
• Partner closely with hardware, SoC, and platform engineering teams to:
• Evaluate and select sensors, compute platforms, and acceleration technologies.
• Define system architectures that balance performance, power consumption, cost, and scalability.
• Ensure robust timing, synchronization, communication, and bandwidth management.
• Collaborate with autonomy, localization, planning, controls, and safety teams to establish system interfaces, requirements, data contracts, diagnostics, and performance expectations.
• Support build-versus-buy evaluations for sensors, software frameworks, perception technologies, SDKs, and third-party components.
• Work closely with Product Managers, Technical Program Managers, and customers to translate business and operational requirements into technical solutions.
• Define and track system and perception performance KPIs including reliability, latency, availability, robustness, scalability, confidence calibration, and operational performance.
• Ensure systems perform reliably in challenging real-world operating environments, including dynamic obstacles, environmental variability, sensor degradation, and adverse conditions.
• Partner with safety engineering teams to identify hazards, analyze failure modes, and support FMEA, fault injection testing, and degraded-mode operations.
• Establish monitoring, diagnostics, observability, and health assessment strategies to ensure safe and reliable operation.
• Drive continuous improvement through field data analysis, root-cause investigations, corrective actions, and iterative product enhancements.
• Engage with customers, partners, and industry stakeholders to understand use cases, operational requirements, and emerging market needs.
• Support pilots, demonstrations, proof-of-concept activities, and customer escalations.
• Communicate technical capabilities, limitations, risks, and trade-offs clearly to both technical and non-technical audiences.
• Incorporate customer feedback and field learnings into product strategy, roadmap planning, and engineering priorities.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical/Computer Engineering, Systems Engineering, or a related technical field.
• 10+ years of experience developing embedded systems for robotics, automotive, consumer electronics, or related products.
• 3+ years of engineering leadership and people management experience leading systems and software development teams.
• Proven experience managing, mentoring, and developing high-performing engineering organizations.
• Strong technical expertise in systems engineering, embedded software, and product development best practices.
• Experience leading cross-functional development across hardware, software, systems, safety, and product management teams.
• Strong understanding of system architecture, sensor integration, and software platforms.
• Proven ability to drive end-to-end ownership, technical execution, roadmap planning, and team accountability.
• Demonstrated success resolving complex technical challenges and delivering products on schedule and at scale.
• Strong communication, collaboration, and stakeholder management skills.
• Experience building engineering roadmaps, resource plans, and organizational capabilities aligned with business objectives.
• Track record of fostering a culture of engineering excellence, continuous improvement, accountability, and talent development.

Nice to have

• Experience with robotics software frameworks and middleware, including ROS and ROS 2.
• Familiarity with modern software development methodologies, including Agile, CI/CD, automated testing, and DevOps practices.
• Working knowledge of perception, sensor processing, computer vision, and machine learning technologies used in autonomous systems.
• Experience deploying and managing ML-based perception systems in production environments, including safety-relevant or human-adjacent applications.
• Experience optimizing software and ML inference workloads on embedded compute platforms, GPUs, NPUs, DSPs, or other hardware accelerators under real-time constraints.
• Experience with system architecture, systems engineering, requirements analysis, and Model-Based Systems Engineering (MBSE).
• Familiarity with industry standards and processes such as Automotive SPICE, ISO 26262, functional safety, and robotics safety-critical system development.
• Experience with cybersecurity principles and secure embedded system design, including encryption, TLS, wireless communication security, and network protection mechanisms.
• Familiarity with microprocessor- and DSP-based hardware architectures, embedded software platforms, and hardware/software integration.
• Experience with embedded communication interfaces and protocols.
• Experience with requirements management processes and tools such as Polarion, DOORS, or equivalent platforms.
• Proven track record of translating customer requirements into production-ready products and engineering solutions.
• Experience working in startup, incubation, or high-growth environments requiring strong ownership, adaptability, and comfort operating in ambiguity.