Software Senior Engineer

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Software Senior Engineer, Software EngineeringAI Innovation Lab

In the rapidly evolving Artificial Intelligence era, few domains are advancing faster than the AI-enabled PC. As a leading provider of world-class technology, Dell Technologies is driving intelligence deeper into the PC ecosystem — delivering superior performance, enhanced productivity, and delightful user experiences while upholding privacy and security.

What you’ll achieve: 

TheAI Innovation Lab is CSG's engine of applied AI — delivering end-to-end AI solutions and earning the position as the most secure and reliable place to run AI agents and solutions, from the device in the hand to the private stack behind the perimeter.

We are hiring aSenior Software Engineer to join the AI Innovation Lab and contribute to our portfolio of applied AI initiatives spanning edge AI, agentic solutions, model evaluation, and intelligent workload orchestration.

Take the first step towards your dream career 

Every Dell Technologies team member brings something unique to the table. Here’s what we are looking for with this role: 

Essential Requirements 

• Bachelor’s degree + 5 years, Master’s + 3 years, or PhD in Computer Science, Engineering, AI/ML, or related fields.
• Strong proficiency inPython, RUST andC++ for backend, apps and performance-critical components.
• Experience withshell scripting for automation and system orchestration.
• Proven expertise inbackend service development andAPI design.
• Hands-on experience withKubernetes (K8s) andDocker for container orchestration and deployment.
• Solid understanding ofSoftware Development Life Cycle (SDLC) and agile methodologies.
• Experience developing forMicrosoft Windows OS, including SDKs and embedded device development in RTOS environments.
• Strong knowledge ofembedded systems and their application in client ecosystems.

Desirable Requirements 

• Experience withAI software development tools, such as model quantization frameworks, inference optimization libraries, or agentic AI platforms.
• Familiarity with development in real-time embedded environments and major hardware vendor toolchains (e.g., Intel OpenVino, Qualcomm QNN, NVIDIA CUDA, AMD Ryzen AI Software).
• Prior work onmodel evaluation frameworks or benchmarking systems for edge AI.
• Experience withLLM inference serving frameworks (e.g., vLLM, Ollama, SGLang) for local and edge AI deployment.
• Exposure toagentic AI workflows, tool-use patterns, or agent harness development.
• Familiarity withhybrid AI orchestration — routing workloads across device, edge, and cloud tiers.