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Tier-1 brand, mid-level role, and metro location increase applicant density but niche embedded+LLM skills limit competition.
Combined ML/LLM expertise with deep embedded/SoC and driver experience is highly domain-specific and poorly transferable.
Explicit 5+ years requirement plus mandatory embedded, device-driver, and LLM skills create highly selective filters.
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Design, develop, and deploy Agentic AI solutions to automate and enhance software engineering workflows spanning code generation, testing, debugging, and release management.
Develop AI applications leveraging large language models (LLMs), retrieval-augmented generation (RAG), agent orchestration, and integrate AI solutions with source control, issue tracking, and CI/CD pipelines.
Collaborate with cross-functional teams including software, hardware, architecture, and infrastructure to identify and implement high-impact AI automation opportunities in embedded systems and SoC platform enablement.
Bachelor's degree in Engineering, Computer Science, Electrical Engineering or related field (Master's or PhD also accepted) with corresponding software engineering experience.
5+ years of experience in software development, embedded systems, platform software, or AI-based solutions; Minimum 2+ years programming experience in C, C++, Java, or Python.
Strong proficiency in Python and/or C++ and hands-on experience developing AI applications using modern LLM frameworks and AI workflow orchestration.
In-depth embedded systems expertise including embedded Linux, Android, RTOS, device driver development/debugging, ARM and/or RISC-V architectures, and SoC bring-up/debugging.
Strong combined expertise in Agentic AI, multi-agent systems, LLMs, and embedded software engineering with ARM/RISC-V architecture knowledge.
Experience building AI-powered engineering automation tools that enhance developer productivity, testing, debugging, and release management.
Technical operating style characterized by cross-domain collaboration between AI and low-level system software to drive impactful AI integration in complex engineering environments.