Software Engineer | Solution Validation, Benchmarking & Release Engineer | 10+ years

Meet the Team

We are a small, agile, and highly collaborative team at the forefront of AI Infrastructure Automation and Benchmarking & Certification. We partner closely with leading hardware and software vendors to design, validate, and deliver curated AI infrastructure solutions to our customers — all built on proven reference architectures that reduce risk and accelerate time-to-value.

Because we're a lean team, every member has real ownership and visibility into outcomes — from automating complex infrastructure workflows to running rigorous benchmarking and certification processes that ensure our solutions perform reliably at scale. We move fast, communicate openly, and lean on each other's expertise daily, making this a great environment for engineers who want to work across the full stack of AI infrastructure rather than being siloed into one narrow function.

Your Impact 

As a Software Engineering Technical Leader, you will own CVIS/NVIS, AI Cluster Validation, end-to-end solution testing, RA certification, GPU debugging, performance profiling, bottleneck analysis, acceptance criteria, test plan and automation, release qualification, and readiness across AI cluster and Cisco network-switch solutions. You will:

• Develop test plans, validation matrices, automation, and exit criteria for AI cluster solutions.
• Execute CVIS/NVIS, AI Cluster Validation, GPU burn, NCCL, workload, resilience, and interoperability test suites.
• Model workloads, profile end-to-end performance, analyze bottlenecks, and produce benchmark reports.
• Validate Cisco network-switch, multi-plane, ToR, compute, storage, and software integrations.
• Drive defect triage, evidence collection, release qualification, RA certification, and acceptance-report packaging.

Minimum Qualifications: 

• Bachelors + 8 years of related experience, or Masters + 6 years of related or equivalent related work experience.
• Experience building and executing end-to-end validation for GPU or distributed AI systems.
• Experience with test strategy, automation, Python, Linux, performance analysis, and defect-triage skills.
• Prior experience translating system requirements into measurable tests, acceptance criteria, and release gates.
• Experience with technical writing and cross-functional communication.

Preferred Qualifications

• CVIS/NVIS, NVIDIA GPU platforms, NCCL, Kubernetes, Slurm, network testing, and storage validation.
• Benchmark engineering, workload modeling, CI-based testing, observability, and release management.
• Experience with Cisco networking and AI cluster reference architectures.

Why Cisco? 

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. 

We are Cisco, and our power starts with you. 

Disclaimer

To ensure that we hire the best talent in the right way, we follow a strict hiring process and recently, Cisco has been made aware of fraudulent recruiters claiming to be from the company. Please be advised that any communication from Cisco about careers will:

• be in direct response to an application you have submitted through the company career site
• begin with screening or an interview
• originate from a Cisco email address, and
• be conducted across email, phone, or WebEx

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