IT & Software

Principal Software Engineer

Microsoft

London · Greater London · United Kingdom

Overview

You will deliver production-ready AI-enabled solutions by embedding within customer teams. In this role you build reliable systems and scalable services, guiding end-to-end architecture from design to deployment. You work with cross-functional crews to translate business needs into technical outcomes and drive customer success at scale. You apply cutting-edge AI and secure engineering practices to impact enterprise outcomes and contribute to Microsoft’s mission of empowering every person and organization.

Responsibilities
  • Prioritize security by designing and shipping solutions that meet enterprise standards
  • Collaborate with stakeholders to translate business needs into architectural approaches and success metrics
  • Own end-to-end system design for cloud and AI workloads with tradeoffs across reliability, performance, and cost
  • Deliver rapidly using CI/CD, automated testing, and observability while managing operational risk
  • Work with customer engineering teams to ensure adoption and measurable outcomes at scale
  • Create reusable assets, accelerators, and reference architectures for broader use
  • Navigate ambiguity, bring clarity, and maintain momentum across complex engagements
  • Provide technical leadership, mentor engineers, and collaborate across product, data, and security teams
  • Coordinate multiple workstreams to improve reliability and production-grade operations
  • Model inclusive leadership and represent the company professionally to external stakeholders
Key requirements
  • Bachelor's Degree in Computer Science or related field and coding experience in C, C++, C#, Java, JavaScript, or Python
  • Experience partnering with customers or internal stakeholders to deliver end-to-end solutions
  • Experience designing, deploying, and operating AI or LLM-based solutions, including prompt engineering and model tuning
  • Familiarity with deploying and operating AI systems in production environments
  • Experience using cloud AI platforms (Azure ML, OpenAI, or similar) and evaluating data quality and performance monitoring
  • Willingness to travel up to 25%
  • leadership
  • collaboration
  • communication
  • AI/LLM solution design and deployment
  • prompt engineering
  • retrieval-augmented approaches

Reference: WJ-747_30233853

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