Senior Embedded Software Engineering Specialist – AI

Responsibilities

• Develop, design, implement, deploy and test AI‑centered solutions for embedded devices and systems development workflows.
• Gather and analyze user/client requirements to create AI‑centered solutions.
• Design, implement, create, test and review software for AI‑centered solutions within a development team.
• Develop and execute communication strategies for AI tool adoption across engineering teams.
• Manage priorities within the development team.
• Teach and assist developers within the team.
• Train and support end users on AI tools and developed solutions.
• Evaluate AI systems and tools.
• Evaluate and select appropriate AI deployment architectures (cloud, on‑premise, edge).

• Bachelor’s degree in Computer Engineering, Electrical Engineering or Computer Science.
• Experience with AI technology development.
• Knowledge of Large Language Models, prompt engineering, retrieval‑augmented generation (RAG), and agentic workflows.
• Experience with embedded C, C++ and Python.
• Experience with software test frameworks, such as Google Test and PyTest.
• Experience with version control systems, such as Git.
• Experience with object‑oriented design.
• Experience with debuggers (Lauterbach/GDB).
• Experience with architecture and design across multiple products or systems.
• Ability to evaluate software architecture alternatives and articulate trade‐offs.
• Experience with system design for embedded, cloud, and API‑based solutions.
• Ability to estimate cost and effort for proposed designs.
• Experience facilitating design reviews and walkthroughs.
• Experience leading requirements gathering and documentation.
• Ability to drive requirement analysis activities from discovery through deliverables.
• Experience translating user needs into technical specifications.
• Experience with alternative troubleshooting approaches across hardware, software and communications systems.
• Ability to lead resolution of complex, multi‑component failures.
• Experience developing troubleshooting standards and best practices.
• Experience diagnosing non‑recurring and performance‑related problems.
• Ability to communicate technical information effectively with team members.
• Ability to host and participate in community practice for engineering communities.
• Ability to work with a cross‑functional team across different disciplines.

Demonstrates expertise in developing and implementing AI‑centered solutions for embedded devices, with a strong focus on user requirements analysis, software architecture evaluation, and effective communication strategies for tool adoption. Proficient in leading development teams and facilitating design reviews while ensuring adherence to best practices in software testing and troubleshooting.