Software Engineer II/Sr. Software Engineer

Microsoft•Redmond, WA
•$102,100 - $261,000

About The Position

The AI Transformation team within Microsoft Frontier Company is reimagining how the company operates in the age of AI. The team works across the business to transform critical end-to-end workflows by bringing people, AI agents, and systems together. It combines engineering, applied AI, program leadership, and business transformation to move from opportunities to working solutions, with a builder mindset that is hands-on, collaborative, comfortable with ambiguity, and action-oriented. Its goal is to build AI-native operating models and reusable solutions that improve operations and accelerate transformation at scale. As a Software Engineer II/Senior Software Engineer, you will apply software design and engineering expertise to build AI-powered solutions that transform company operations. You will work in small, multidisciplinary teams to move solutions from prototype to production, using AI and agentic coding tools to build reliable applications, agents, integrations, and workflows that deliver measurable operational impact.

Requirements

  • Bachelor's degree in computer science or a related technical field and at least 2 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.

Nice To Haves

  • Bachelor's degree in computer science or a related technical field and at least 4 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
  • Master's degree in computer science or a related technical field and at least 2 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.

Responsibilities

  • Design, build, test, deploy, and operate production-grade AI-powered applications, agents, services, integrations, and workflows.
  • Move from requirements and ideas to working solutions, prototyping and iterating based on real-world feedback while maintaining reliability, performance, and maintainability.
  • Use AI-assisted and agentic coding tools throughout the software development lifecycle to accelerate development, testing, debugging, experimentation, and delivery.
  • Translate business and operational requirements into practical technical designs and scalable implementations in collaboration with engineers, applied scientists, TPMs, designers, and operational teams.
  • Apply software engineering practices including code reviews, automated testing, CI/CD, observability, documentation, and operational readiness.
  • Build reusable components, accelerators, and engineering patterns to help solutions scale across teams and transformation scenarios.
  • Adapt in ambiguous, fast-moving environments, experiment with emerging AI technologies, and improve solutions based on measurable outcomes.
  • Apply a security-first mindset and incorporate privacy, Responsible AI, compliance, and Microsoft engineering requirements throughout design and delivery.
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