Cloud Software Development Engineer

Intel•Hillsboro, OR

1d•$128,880 - $245,160•Hybrid

About The Position

As a Cloud Software Development Engineer in the System Simulation and Modeling (SSM) organization, you will design, develop, and optimize software solutions that enable Intel's next generation platforms before silicon is available. You will contribute to innovations in simulation, system software, automation, and cloud infrastructure that accelerate firmware and software development across Intel product lines. In this role, you will work closely with firmware engineers, operating system developers, architects, silicon designers, and software teams to develop high-fidelity development environments and shift-left solutions that improve product quality, reduce execution risk, and accelerate time-to-market. Your work will directly contribute to Intel's skills to develop, integrate, validate, and optimize complex system software stacks in a modern cloud-based development ecosystem. You will be expected to independently drive technical solutions, solve complex system-level problems, and deliver high-quality software from design through deployment. The System Simulation and Modeling (SSM) team is part of the Product Enablement Solutions Group (PESG). We are transforming how Intel firmware and software are developed, integrated, and validated through advanced simulation, modeling, automation, and cloud technologies. Our team develops large-scale system simulation platforms that enable software development and validation months before silicon availability. These capabilities are critical to Intel's product execution strategy, reducing schedule risk while accelerating innovation across Data Center, AI, and emerging platform technologies.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field with 4+ years of experience.
OR Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field with 3+ years of experience,
OR PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field with 1+ years of experience
Experience should be in: Software development or related technical disciplines.
Developing and debugging software solutions in large-scale development environments.
Computer architecture and system software concepts.
C++, Python, or similar programming languages.
Executing technical projects and solving complex engineering problems.

Nice To Haves

Experience with system simulation, virtual platforms, modeling technologies, or emulation environments.
Knowledge of computer architecture domains such as RAS, Memory Technologies, Security, I/O subsystems, Accelerators, GPUs, or AI platforms.
Experience debugging firmware, operating systems, device drivers, or other low-level software.
Experience with cloud-native development, distributed systems, Kubernetes, containers, or modern DevOps practices.
Experience applying AI/ML technologies to software engineering workflows, automation, or developer productivity.

Responsibilities

Design, develop, debug, validate, and optimize software solutions supporting simulation, system modeling, automation, and cloud-based development environments.
Collaborate with cross-functional teams to understand firmware, drivers, operating systems, middleware, and SDK requirements and deliver solutions that enable shift-left development.
Develop scalable software and automation frameworks that improve developer productivity and product readiness.
Analyze and resolve complex technical issues involving system software, simulation environments, firmware, and hardware-software interactions.
Apply AI-assisted development practices and automation techniques to improve engineering efficiency and software quality.
Exercise sound technical judgment to remove obstacles, evaluate tradeoffs, and deliver robust solutions.
Identify opportunities to improve performance, reliability, automation, and scalability across development workflows.
Participate in technical reviews and contribute to engineering best practices across the team.