Overview

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.

Responsibilities

• 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.

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.