The Principal Software Engineer, Intelligent Quality Solutions joins the Enterprise Quality Engineering organization to build an AI-native quality engineering ecosystem. As a senior individual contributor, you will develop intelligent applications, AI-enabled services, APIs, and reusable frameworks that form the foundation of the Enterprise Quality Intelligence Platform. Your daily work involves engineering production-ready software, creating autonomous agents to improve testing productivity, and integrating AI capabilities into software development workflows. You will utilize large language models, generative AI, machine learning, and modern AI orchestration frameworks like Azure OpenAI or Anthropic Claude. Key technical skills include cloud-native architectures, distributed systems, retrieval-augmented generation, and vector databases. You will solve complex technical challenges by establishing best practices for AI governance, security, and observability within a highly regulated industry context.
What does a Software Engineer earn in Remote?
Median $208800 from 354 postings across 50 companies.
Develop AI-powered software solutions, services, and APIs for Enterprise Quality Engineering.
Create and enhance autonomous agents to improve software testing and engineering productivity.
Build scalable, secure, and production-ready enterprise software and reusable frameworks.
Integrate AI capabilities into existing software development and quality engineering processes.
Evaluate new AI technologies and prototype solutions for enterprise use.
Provide technical leadership, architecture guidance, and mentorship across engineering projects.
Establish best practices for AI development, governance, security, and observability.
What we're looking for
Bachelor's degree in Computer Science, Software Engineering, Engineering, or a related field.
Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field (preferred).
12 or more years of experience designing and building enterprise software applications, services, or platforms.
Hands-on experience designing, developing, deploying, and supporting AI-powered software applications in production environments.
Demonstrated experience building applications using large language models, generative AI, agentic AI, machine learning, or modern AI orchestration frameworks.
Strong software engineering expertise across cloud-native architectures, APIs, distributed systems, modern design patterns, and secure software development.
Experience building scalable enterprise platforms, reusable enterprise capabilities, or internal engineering products (preferred).
Experience with RAG, vector databases, semantic search, prompt engineering, or enterprise AI platforms like Azure OpenAI (preferred).
Python
C#
Java
C++
JavaScript
Generative AI
Large Language Models
Agentic AI
Azure AI Foundry
Copilot Studio
Power Platform
Retrieval-Augmented Generation
Prompt Engineering
Distributed Systems
APIs
Observability
Data Governance
Video Coding
AV1
AV2
AVC
HEVC
VVC
Deep Learning
Computer Vision
C++
Python
gStreamer
Docker
REST APIs
XML
JSON
Git
GitHub
ABR Algorithms
Video Processing