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Software Principal Engineer

Job Description - Software Principal Engineer

Description

Principal Engineer, Software Engineering 

The Software Engineering team delivers next-generation software application enhancements and new products for a changing world. Working at the cutting edge, we design and develop software for platforms, peripherals, applications and diagnostics — all with the most advanced technologies, tools, software engineering methodologies and the collaboration of internal and external partners. 
 

What you’ll achieve: 
As a Software Principal Engineer, you will develop advanced modules, optimize performance, and contribute to architectural choices. You will collaborate across teams to deliver robust, secure solutions. 
 

Join us to do the best work of your career and make a profound social impact as a Principal Engineer on our Software Engineering team in Austin, Texas. 
 



Responsibilities

You will: 

  • Design, build, and deploy intelligent AI agents that can reason, plan, execute actions, and collaborate across enterprise systems.
  • Develop advanced modules and optimize runtime performance.
  • Contribute to architectural decisions and integration patterns.
  • Perform code reviews and uphold quality/cohesion.
  • Collaborate across teams for feature delivery.


Qualifications

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 

  • 8+ years of related experience
  • Advanced coding and debugging in core languages/frameworks.
  • Experience working with LLMs such as OpenAI, Azure OpenAI, Anthropic, Google Gemini, or equivalent.
  • Experience building APIs and cloud-native applications.
  • Knowledge of prompt engineering, RAG, embeddings, vector databases, and AI orchestration frameworks.

 

Desirable Requirements 

  • Experience with Semantic Kernel, LangGraph, AutoGen, CrewAI, or similar agent frameworks.
  • Knowledge of AI observability, evaluation frameworks, and model monitoring.


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