Software Engineering

In this role you will build production-grade software and services within a forward-deployed model that embeds engineers with customer teams. You will apply AI and data-driven methods to deliver scalable, secure solutions that drive business outcomes. You’ll work with cross-functional colleagues and own the end-to-end lifecycle from design to deployment. This is a hands-on, fast-moving environment focused on impact, security, and quality. You will contribute to reusable patterns and trusted customer outcomes at scale.

• Design, build, test, and operate production-grade software and services that are secure, reliable, and scalable
• Partner with customers and internal stakeholders to clarify requirements and translate business needs into technical designs
• Drive engineering best practices including code reviews, automated testing, CI/CD, observability, and documentation
• Apply a security-first mindset and follow security and compliance requirements throughout design and delivery
• Deliver customer outcomes end-to-end: prototype quickly, iterate with feedback, and land quality solutions
• Build reusable components, reference implementations, and patterns for cross-team use
• Learn and adapt in a fast-moving environment using experimentation and data for continuous improvement
• Collaborate across disciplines (engineering, data science, product, design, security) and foster an inclusive team culture
• Lead technical workstreams by aligning stakeholders and driving delivery
• Embeddable with Microsoft values and culture in daily work

• Bachelor's Degree in Computer Science or related technical field and experience with coding in C, C++, C#, Java, JavaScript, or Python
• Experience partnering directly with customers or internal stakeholders to deliver end-to-end solutions
• Equivalent experience may be considered

• Collaboration across disciplines
• Strong communication and stakeholder management
• Adaptability in fast-moving environments
• C, C++, C#, Java, JavaScript, Python
• AI/LLM-based solution design: prompt engineering, retrieval-augmented approaches, model tuning
• Data quality, evaluation, and performance monitoring