Software Engineer – SONiC & Network Systems

Company: Upscale AI
Team Size: +100 employees
Industry: High-Tech / Emerging Infrastructure
Department: AI Network Software
Location: Bangalore, India

Why join Upscale AI

Upscale AI is building high-performance infrastructure powering the next generation of artificial intelligence. Backed by over $300M in funding and rapid global adoption, we are scaling systems designed for the world’s most demanding AI workloads.

We focus on first-principles engineering across silicon, systems, and networking—where performance, scale, and execution are critical. Our team is talent-dense and high-performing. We value ownership, technical rigor, and speed, and we offer the opportunity to work on foundational problems with immediate, real-world impact.

If you’re looking to do high-impact work, move fast, and help define the infrastructure behind the future of AI—Upscale AI is where you can produce meaningful work at the frontier—and operate at a high standard.

Position Overview

We are seeking a talented and experienced Software Engineer with deep expertise in SONiC (Software for Open Networking in the Cloud) network operating system (NOS), Layer 2/Layer 3 networking, and network test frameworks including PTF and SPyTest. In this role, you will be a key contributor to the development, validation, and optimization of modern network operating systems, helping drive innovation in data center and enterprise network infrastructures built for AI/ML applications.

Key Responsibilities

• Design, develop, and maintain features and enhancements for the SONiC NOS platform.
• Develop and execute test plans using PTF and SPyTest for L2/L3 networking protocols and infrastructure.
• Debug, troubleshoot, and resolve complex networking issues at scale on SONiC platforms.
• Collaborate closely with cross-functional teams including hardware engineers, QA, and DevOps to ensure seamless integration and deployment.
• Participate in code reviews, architecture discussions, and documentation efforts.
• Contribute to SONiC open-source communities and stay current with the evolving SONiC ecosystem

Requirements

• Bachelor’s or Master’s degree in Computer Science, Electrical Engg., or a related field.
• Minimum 5 years of hands-on experience in network software development.
• Strong experience with SONiC network operating system.
• Proficient in Python, C/C++, Go.
• Experience with PTF (Packet Test Framework) and SPyTest for network validation.
• Familiarity with Linux internals, docker containers, and network virtualization technologies.
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.

Preferred Skills

• Contributions to the SONiC open-source community.
• Experience with Software Defined Networking (SDN) controllers and programmable data planes.
• Knowledge of network ASICs and switch hardware architecture.
• Solid understanding of Layer 2 and Layer 3 networking protocols (e.g., VLANs, STP, BGP, OSPF).

Compensation

Where you fall within our ranges depends on your experience, skills, and impact—we benchmark against internal levels to keep things fair and consistent.

Upscale AI is an Equal Opportunity Employer that is committed to inclusion and diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, disability or protected veteran status. We also take affirmative action to offer employment opportunities to minorities, women, individuals with disabilities, and protected veterans.

Upscale AI is committed to working with qualified individuals with physical or mental disabilities. Applicants who would like to contact us regarding the accessibility of our website or who need special assistance or a reasonable accommodation for any part of the application or hiring process may contact us at: hiring@upscaleai.com. This contact information is for accommodation requests only. Evaluation of requests for reasonable accommodation will be determined on a case-by-case basis.