Staff Engineer – AI in Embedded Software Development Lifecycle (SDLC)
Location: Pune, India
About GF
GlobalFoundries (GF) is a leading manufacturer of essential semiconductors, enabling AI at scale from the cloud to the physical world. Through deep partnerships with customers, GF delivers differentiated, power-efficient and high-performance solutions for high-growth markets. With global manufacturing operations across the U.S., Europe and Asia, GF is a trusted technology partner for customers around the world. GF's talented global team remains focused every day on security, longevity, and sustainability. For more information, visit www.gf.com.
Introduction
GlobalFoundries is seeking a highly motivated Staff Engineer to lead the adoption of Artificial Intelligence across the embedded software development lifecycle. This role combines deep expertise in embedded systems with practical experience applying Large Language Models (LLMs), Small Language Models (SLMs), Retrieval-Augmented Generation (RAG), and AI-powered automation to accelerate software development, validation, and product delivery.
The successful candidate will serve as a technical leader driving the integration of AI-enabled workflows across platform software, firmware, test, and validation teams. This position requires strong hands-on experience in embedded software development, AI/ML technologies, and engineering productivity tooling, enabling the transformation of how software is designed, implemented, tested, documented, and maintained.
Your Job
- Define and drive the technical strategy for AI adoption across the embedded software development lifecycle, including requirements, design, coding, testing, validation, documentation, and release activities.
- Develop AI-powered solutions that generate embedded software components such as low-level drivers, hardware abstraction layers (HALs), BSP integrations, register-access layers, and validation utilities from specifications and hardware documentation.
- Design and deploy Retrieval-Augmented Generation (RAG) systems utilizing source code, technical documentation, silicon specifications, issue-tracking systems, and historical validation data.
- Build and fine-tune Small Language Models (SLMs) and LLM-based solutions for embedded software generation, test automation, defect triage, and engineering productivity enhancement.
- Develop automated pipelines that convert requirements and design specifications into executable embedded test cases, validation frameworks, and simulation scripts.
- Create AI-based solutions for post-silicon validation, including log analysis, anomaly detection, failure clustering, regression triage, and root-cause assistance.
- Integrate AI-enabled tooling into engineering workflows, source control systems, code review processes, IDEs, CI/CD environments, and validation frameworks.
- Establish model evaluation methodologies and quality metrics focused on correctness, code quality, coverage improvements, build success rates, productivity gains, and developer adoption.
- Define governance, traceability, security, IP protection, and compliance controls for AI-generated software artifacts in safety-critical development environments.
- Provide technical leadership, mentorship, and AI enablement across software, architecture, validation, and platform engineering teams.
Other Responsibilities
- Perform all activities in a safe and responsible manner and support all Environmental, Health, Safety & Security requirements and programs.
- Support engineering excellence through collaboration, knowledge sharing, and continuous process improvements.
- Maintain compliance with company quality standards, development processes, and product security requirements.
Required Qualifications
- Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, Artificial Intelligence, Machine Learning, or a related technical discipline.
- Minimum 4 to 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 including scheduling, interrupts, synchronization mechanisms, memory management, and low-level driver development.
- Experience with protocols and interfaces such as CAN, LIN, SPI, I2C, UART, Ethernet, or related embedded communication technologies.
- Practical experience with AI/ML frameworks including PyTorch, Hugging Face, LangChain, LlamaIndex, Haystack, or equivalent technologies.
- Experience developing and deploying RAG architectures, vector databases, embeddings, semantic search, and knowledge retrieval systems.
- Proven expertise in model fine-tuning techniques such as LoRA and QLoRA.
- Experience integrating AI solutions into software engineering workflows, developer tools, CI/CD pipelines, and automated validation environments.
- Knowledge of model serving, optimization, quantization, and deployment in on-premises environments.
- Experience with embedded testing, silicon bring-up, HIL validation, system debugging, and hardware/software integration.
- Ability to work effectively across distributed global engineering teams.
- Ability to travel up to 10% as required.
Preferred Qualifications
- Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, or related field.
- Experience with RISC-V processor architectures, toolchains, and ecosystem development.
- Knowledge of AUTOSAR, safety-critical systems, and functional safety standards including ISO 26262.
- Experience developing IDE plugins, engineering productivity tools, or software developer platforms.
- Experience with MLOps infrastructure, GPU-based training and 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 projects, or providing technical thought leadership in AI-assisted engineering.
- Experience working with semiconductor product development, post-silicon validation, or firmware platform teams.
GlobalFoundries Equal Opportunity Statement
GlobalFoundries is an equal opportunity employer, cultivating a diverse and inclusive workforce. We believe having a multicultural workplace enhances productivity, efficiency and innovation whilst our employees feel truly respected, valued and heard. As an affirmative employer, all qualified applicants are considered for employment regardless of age, ethnicity, marital status, citizenship, race, religion, political affiliation, gender, sexual orientation and medical and/or physical abilities. All offers of employment with GlobalFoundries are conditioned upon the successful completion of background checks, medical screenings as applicable and subject to the respective local laws and regulations.
No Recruitment Fee Policy
GlobalFoundries is committed to ethical and transparent hiring practices. Candidates will not be charged any fees at any stage of the recruitment process. Any request for payment related to a GlobalFoundries employment opportunity is unauthorized and should be reported immediately. All legitimate recruitment communications are conducted exclusively through official GlobalFoundries channels. To report concerns or suspected recruitment fraud, please contact the Ethics & Compliance Office at global.compliance@globalfoundries.com. The Ethics & Compliance mailbox is not a recruitment channel. CVs/resumes submitted to this mailbox will not be reviewed, processed, or considered for employment opportunities. Please apply through the official GlobalFoundries careers site only.
