Staff Engineer – AI in Embedded Software Development Lifecycle (SDLC)

Job Title

Staff Engineer – AI in Embedded Software Development Lifecycle (SDLC)

Role Summary

Lead the technical adoption of AI across the embedded software development lifecycle to accelerate design, implementation, testing, validation, and release. Work with firmware, platform, test and validation teams to integrate AI-powered code generation, RAG systems, model fine-tuning, and engineering productivity tooling into existing workflows.

Experience Level

Senior - 4 to 8 years of industry experience in embedded software, firmware, or platform engineering.

Responsibilities

Primary responsibilities focus on defining strategy, building AI-enabled tooling, and integrating those solutions into engineering processes.

• Define and drive AI adoption strategy across requirements, design, coding, testing, validation, documentation, and release activities.
• Develop AI-driven generation tools for low-level drivers, HALs, BSP integrations, register-access layers, and validation utilities from specifications and hardware docs.
• Design and deploy Retrieval-Augmented Generation (RAG) systems leveraging source code, documentation, silicon specs, issue trackers, and historical validation data.
• Build and fine-tune Small Language Models (SLMs) and LLM-based solutions for code generation, test automation, defect triage, and productivity improvements.
• Create automated pipelines to convert requirements and designs into executable test cases, validation frameworks, and simulation scripts.
• Develop AI techniques for post-silicon validation: log analysis, anomaly detection, failure clustering, regression triage, and root-cause assistance.
• Integrate AI tooling into source control, code review, IDEs, CI/CD, and validation frameworks; define model evaluation metrics and measurement strategies.
• Define governance, traceability, security, IP protection, and compliance controls for AI-generated artifacts in regulated/safety-critical contexts.
• Provide technical leadership, mentorship, and enablement across software, architecture, validation, and platform teams.

Requirements

Must-have skills and experience.

• 4–8 years of industry experience in embedded software development, firmware engineering, platform software, or related fields.
• Strong proficiency in C/C++ and Python.
• Hands-on experience developing embedded software for microcontrollers, microprocessors, automotive systems, or embedded Linux platforms.
• Strong understanding of RTOS concepts: scheduling, interrupts, synchronization, memory management, and low-level driver development.
• Experience with embedded protocols and interfaces such as CAN, LIN, SPI, I2C, UART, and Ethernet.
• Practical experience with AI/ML frameworks and tools (examples: PyTorch, Hugging Face, LangChain, LlamaIndex, Haystack) and deploying RAG architectures, vector databases, embeddings, and semantic search.
• Proven expertise in model fine-tuning techniques such as LoRA and QLoRA; experience with model serving, optimization, quantization, and on-premises deployment.
• Experience integrating AI solutions into developer workflows, CI/CD pipelines, developer tools, and automated validation environments.
• Experience with embedded testing, silicon bring-up, HIL validation, system debugging, and hardware/software integration.
• Ability to work across distributed global engineering teams and travel up to 10%.

Nice-to-have:

• Experience with RISC-V architectures, toolchains, and ecosystem development.
• Familiarity with AUTOSAR, functional safety standards (e.g., ISO 26262), or safety-critical systems.
• Experience developing IDE plugins, engineering productivity tools, or developer platforms.
• Experience with MLOps infrastructure, GPU-based training/inference environments, and enterprise AI deployments.
• Exposure to static code analysis, compiler technologies, program analysis, or code intelligence platforms.
• Expertise in AI governance, security, model evaluation, traceability, and responsible AI practices.
• Experience publishing research, contributing to open-source, or technical thought leadership; experience with semiconductor product development or post-silicon validation teams.

Education Requirements

Required: Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline. Preferred: Master's or Ph.D. in Computer Science, AI/ML, Electrical Engineering, or a related field.

About the Company

Company: GlobalFoundries

Headquarters: Saratoga Springs, New York, USA

GlobalFoundries is a leading contract manufacturer for the global semiconductor industry, with facilities in multiple countries, including the USA. The company develops a broad portfolio of semiconductor technologies and employs around 13,000 people worldwide. GlobalFoundries focuses on enhancing competitiveness in specialized application solutions and fostering innovation in mobile communications, consumer electronics, and automotive applications.