Robotics Engineer Manager

Engineering Manager – Robotics (Software, Hardware, Systems, AI & Functional Safety)

Role Overview

You’ll lead a new multi-disciplinary engineering group building embedded and full-stack systems for advanced robotics. This includes direct responsibility for functional safety across software, hardware, systems and AI. The role blends people leadership with technical judgement, ensuring the entire robotics stack is engineered to behave predictably, safely and reliably in real-world environments.

Core Responsibilities

Leadership & Delivery

• Build and lead an engineering organisation across embedded software, electronics, mechanical systems, AI/ML and full-stack.
• Set engineering direction: architecture, development practices, release processes, testing, reliability and safety.
• Drive delivery of robotics platforms from concept through to field deployment, ensuring the system is safe, stable and maintainable.
• Make clear technical trade-offs between performance, complexity, deadlines and safety constraints.

Robotics Functional Safety (Key Additions)

• Own functional safety for the robotics platform, ensuring compliance with relevant standards (e.g., ISO 13849, IEC 61508, ISO 10218, or equivalent depending on application).
• Define, maintain and enforce safety requirements: hazard analysis, risk assessments (FMEA, HARA), safety goals, redundant architectures and safe-state behaviours.
• Work with hardware, embedded and AI teams to ensure the entire control loop — sensing, actuation, perception, autonomy, and fallback modes — meets the required safety levels.
• Oversee safety case development, verification and validation plans, and documentation needed for certification or regulatory submissions.
• Ensure safety is designed in from the start, not bolted on at the end.

Cross-Disciplinary Integration

• Ensure software, hardware, AI and full-stack work as a unified system rather than separate technical islands.
• Run system-level reviews covering compute, power, thermal, sensing, networking, autonomy pipelines, safety architecture and reliability.
• Coordinate hardware/firmware bring-up, integration testing, subsystem validation and release schedules.

Technical Oversight

• Guide architecture for embedded systems (C/C++/Rust, microcontrollers, RTOS/Linux, comms protocols).
• Direct AI/ML integration: model selection, inference optimisation, fail-safe behaviour and limitations under real-world constraints.
• Support backend/cloud/data components: APIs, logging, telemetry, diagnostics, update pipelines, and system observability.
• Ensure system robustness, fault tolerance, recoverability and in-field reliability.

Team Development

• Hire and develop engineers across disciplines; set clear expectations and create a focused environment where people can execute without noise.
• Coach leads on technical decision-making, planning and safety-driven engineering discipline.
• Mature the team from fast prototyping into repeatable, controlled engineering cycles.

Operations & Process

• Implement tight but pragmatic processes for planning, risk tracking, design reviews, documentation and testing — without unnecessary bureaucracy.
• Establish robust engineering workflows including CI/CD suited to embedded and robotics systems, hardware version control, structured system testing and safety validation.
• Work closely with product, manufacturing, field teams and safety assessors to ensure the system is both buildable and certifiable.

Technical Background

• Track record leading multi-disciplinary engineering teams delivering hardware + software products, ideally within robotics.
• Deep familiarity with some of the following; robotics, embedded systems, cloud infrastructure & autonomy software
• Experience integrating AI/ML (perception, control, planning, inference optimisation) into real products.
• Exposure to functional safety engineering (one or more standards): understanding of safety patterns, redundancy, diagnostics, safe states, hazard analysis and verification.
• Clear understanding of backend, APIs, data flows and operator applications that support robotic systems.

Leadership

• Strong judgement: can challenge technical decisions while keeping delivery realistic.
• Skilled at stabilising complex engineering efforts and unblocking teams.
• Able to build a culture of safety, reliability and disciplined engineering without slowing progress unnecessarily.
• Experience hiring, developing and retaining high-calibre engineers across domains.

What Success Looks Like

• Building and championing trust, respect and collaboration within the team and business
• A robotics system that is safe, stable, and ready for real deployment — not just demos.
• Embedded, hardware, AI and full-stack components built around a coherent safety architecture.
• Safety is embedded in engineering decisions, not treated as paperwork or a final-phase task.
• Engineering norms become established: predictable releases, clear ownership, reliable documentation, traceable changes.
• Creating a team that communicates clearly, executes consistently, and delivers world class products
• Certification or internal safety approval processes run smoothly because the underlying engineering is sound.