IT & Software

Senior Software Engineer - FDE

Microsoft

London · Greater London · United Kingdom

Overview

As a Senior Software Engineer in the Frontier Company Engineering team, you design and ship reliable, production-ready systems that turn data-driven ideas into scalable AI-enabled solutions. You work with a cross-functional team to solve complex customer challenges directly in customer environments. You apply modern engineering practices and security-first thinking to deliver high-impact outcomes. This role offers collaboration with global customers and the chance to shape AI-powered platforms at scale.

Responsibilities
  • Prioritize security from design to production, incorporating threat modeling and privacy controls
  • Translate business needs into technical solutions with measurable outcomes
  • Own end-to-end system design for cloud and AI workloads with balance across reliability, performance, cost
  • Deliver rapidly using CI/CD, automated tests, observability, and progressive delivery
  • Drive customer success by delivering production-ready solutions and enabling adoption at scale
  • Create reusable assets, accelerators, and reference architectures for broader impact
  • Operate effectively in ambiguity, bringing clarity and momentum to complex engagements
  • Provide technical leadership, mentoring, and cross-functional collaboration
  • Lead complex, end-to-end delivery with focus on reliability and operational excellence
  • Model inclusive, customer-obsessed leadership and represent the company professionally with external stakeholders
Key requirements
  • Bachelor's Degree in Computer Science or related field plus 6+ years of engineering experience with listed languages or equivalent
  • Experience partnering directly with customers or internal stakeholders to deliver end-to-end solutions
  • collaboration
  • technical leadership
  • customer focus
  • C, C++, C#, Java, JavaScript, or Python
  • AI/LLM-based solution design, deployment, and operations
  • prompt engineering, retrieval-augmented approaches, model tuning, data quality

Reference: WJ-747_30160596

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