We are looking for an experienced and hands-on Embedded Software Group Lead to lead a team developing complex and versatile software solutions. In this role, you will combine technical leadership with hands-on development, guiding projects from concept to production while mentoring engineers and driving architectural decisions.

You will work in a challenging and multidisciplinary technological environment involving diverse software technologies, algorithms, and a broad software stack.

Responsibilities

• Lead, mentor, and grow a team of embedded software engineers
• Drive the design, architecture, and implementation of complex software systems in an embedded Linux environment
• Own end-to-end delivery: from concept, design, and development to integration and production
• Oversee software integration across multiple system components
• Collaborate closely with system, hardware, and cross-functional teams
• Balance hands-on development with leadership responsibilities (design reviews, code reviews, debugging)
• Define and enforce best practices, development processes, and coding standards
• Manage priorities, timelines, and technical risks
• Write and review technical documentation and design specifications

Qualifications

• 7+ years of experience in embedded software development on Linux platforms
• 4+ years of experience in a technical leadership or team lead role
• Strong programming skills in C, C++, and Python
• Vast experience with Linux kernel drivers development
• Deep understanding of HW/SW architecture, OS internals, and HW-SW partitioning
• Proven experience leading complex projects and driving technical decisions
• Strong problem-solving skills and ability to navigate ambiguity
• Experience with development toolchains, debugging tools, and automation frameworks
• Excellent communication skills (verbal and written)
• High level of ownership, accountability, and a proactive mindset

Advantages

• Experience with storage systems (NVMe, block/stream storage)
• Hands-on experience with Linux kernel development and customization
• Familiarity with HW acceleration for AI/ML
• Experience with virtualization (VMs, containers)
• Experience working with ARM Cortex-A CPUs
• Familiarity with Xilinx tools and ecosystem