Senior Software Engineer
MicrosoftAbout the role
At Surface, we create the devices and experiences that empower people to achieve more. Our engineering teams build the platforms, services and tools that enable secure, reliable and innovative product development across hardware, software, cloud, AI and security. We are transforming engineering through AI-powered platforms, modern security practices and scalable developer experiences that accelerate innovation while maintaining Microsoft's high standards for security, privacy and compliance.
We're looking for a Senior Software Engineer to join the Surface Engineering team to build secure, scalable platforms and AI-powered solutions that strengthen security, enable compliance and improve engineering productivity. You will help shape next-generation security capabilities, AI-driven workflows and Secure-by-Design engineering practices across our Engineering Systems.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.
Responsibilities
- Design, build and operate AI-powered software platform services that support security engineering across Surface Engineering Systems.
- Develop AI-enabled workflows that help engineering and security teams analyze information, retrieve relevant context, summarize findings and make faster, higher-quality decisions.
- Build scalable systems that use large language models, retrieval-augmented generation, embeddings, semantic search, knowledge graphs and related AI techniques to support security scenarios.
- Create evaluation, measurement and monitoring approaches that help assess AI system quality, reliability, safety and effectiveness in production environments.
- Partner with engineering, applied science, product, security operations and other teams to translate AI advances into practical, secure, durable and reliable platform capabilities.
- Incorporate responsible AI, privacy, security, and compliance considerations into the design, deployment and operation of AI-powered systems.
- Provide technical leadership through design documents, architecture discussions, code reviews, and collaboration with partner teams.
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
Preferred Qualifications:
- Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR equivalent experience.
- 5+ years of experience building cloud services and distributed systems.
- Experience with Azure, cloud-native architectures, APIs and platform engineering.
- Knowledge of application security, threat modeling, vulnerability management, identity and access management, or software supply chain security.
- Experience building AI-enabled applications using LLMs, RAG, vector search, agents, or related technologies.
- Solid system design, problem-solving, and cross-functional collaboration skills.
- Experience in AI-native engineering practices, with hands-on experience applying AI to develop software solutions across the development lifecycle, including code generation, test automation and related workflows.
- Experience with full-stack development, backend engineering, platform engineering, infrastructure services, or data-driven applications.
- Experience building AI-powered solutions, intelligent automation, LLM-enabled applications, agentic workflows, or leveraging AI-assisted engineering tools.
- Solid product mindset with a track record of owning ambiguous problem spaces and driving them to high-quality outcomes.
- Solid engineering fundamentals, including systems design, performance and debugging in complex production environments.
- Experience building and shipping production software or services.
- Working knowledge of data structures, algorithms, and software design fundamentals.
- Experience with cloud services, distributed systems, web experiences, or large-sca
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