Principal Software Engineer - Finance Data & Experiences

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

Principal Software Engineer at Microsoft focused on AI within the Finance Data & Experiences organization. The role involves leading architecture for complex AI-driven products, improving AI tools and practices in the SDLC, mentoring engineers, driving integration, ensuring security and compliance, and innovating automation for zero-touch deployments. The goal is to leverage AI for business excellence and customer satisfaction, with an emphasis on Responsible AI practices.

What you'd actually do

  1. Lead architecture discussions and design complex AI-driven products, ensuring design choices meet performance, scalability, resiliency, and security requirements.
  2. Mentor engineers and create comprehensive test strategies that incorporate AI-powered automation and security testing to ensure high-quality, reliable software solutions.
  3. Drive integration and collaboration across teams to manage dependencies, security compliance, and performance for AI-enhanced systems.
  4. Establish and enforce security best practices, including proactive deployment gates and AI safety features, and ensure robust security monitoring and incident response.
  5. Innovate and implement automation in production and deployment, targeting zero-touch rollouts for AI-based solutions.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field
  • 6+ years technical engineering experience
  • coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

Nice to have

  • Master's Degree in Computer Science or related technical field
  • 8+ years technical engineering experience
  • 12+ years technical engineering experience
  • Experience with AI capabilities such as Azure OpenAI, Cognitive Services, and machine learning models
  • driving the design, integration, and execution of AI-enabled solutions across programs to enhance system intelligence, improve productivity, and deliver measurable business impact.

What the JD emphasized

  • AI-driven products
  • AI-powered automation
  • AI-enhanced systems
  • AI safety features
  • AI-based solutions
  • AI tools
  • AI advancements
  • AI systems
  • AI capabilities
  • AI-enabled solutions

Other signals

  • AI-driven business excellence
  • improve AI tools and practices throughout the software development lifecycle
  • lead architecture discussions for complex products
  • apply cutting-edge technology
  • implementing AI to drive business excellence