Senior Software Engineer

Commercial Engineering & AI (CEAI) partners closely with stakeholders to accelerate the transformation of Microsoft’s commercial business into a frontier organization. We bring together AI‑native engineering, modern platforms, and deep commercial insight to reimagine how work gets done - at scale and with impact. Our mission is to unlock new ways of operating through intelligent systems while creating the conditions for our teams to do the most meaningful work of their careers.  

The Marketing Growth Engineering team builds and operates the platforms that connect Microsoft’s marketing intent to measurable commercial outcomes. Within this organization, Customer Data Platform Engineering is responsible for creating a trusted, governed, and AI-ready commercial customer. This platform is strategically relevant to Microsoft’s commercial business because it enables high-quality customer engagements and agentic experiences grounded in authoritative customer context. By exposing reusable data products, APIs, Agents and MCP capabilities, the team accelerates into IQ, Copilot, and autonomous capabilities to power the Commercial business. 

• Design, build, and operate scalable full-stack applications and data services that power AI-enabled commercial scenarios. 

• Develop secure APIs, user experiences, data pipelines, and distributed services using modern engineering practices. 

• Partner with product managers, data scientists, and engineering teams to translate business needs into reliable technical solutions. 

• Apply software engineering fundamentals across architecture, coding, testing, deployment, observability, performance, privacy, and security. 

• Use AI-assisted engineering tools and automation to improve developer productivity, solution quality, and delivery speed. 

• Troubleshoot complex production issues, strengthen service reliability, and contribute to operational excellence. 

• Provide technical leadership through design reviews, code reviews, mentoring, and continuous improvement. 

Required/minimum qualifications

Preferred Qualifications

• Experience designing, building, testing, and operating production software or data systems. 

• Experience with data structures, algorithms, distributed systems, APIs, and cloud services. 

• Experience building full-stack applications and large-scale data pipelines on Azure or a comparable cloud platform. 

• Experience with relational and non-relational data stores, data modeling, batch and streaming processing, and service integration. 

• Experience applying AI/ agentic capabilities in production solutions and using AI-assisted development tools. 

• Experience collaborating across disciplines, communicate technical trade-offs, mentor engineers, and deliver secure, reliable services in ambiguous environments. 

• Technical leadership through architecture and design reviews, engineering standards, mentoring, and influencing teams without direct authority. 

• Written and verbal communication skills, with the ability to explain complex technical concepts, tradeoffs, risks, and recommendations to technical and non-technical stakeholders. 

• Experience operating in ambiguous, fast-moving environments by clarifying requirements, defining milestones, making sound decisions with incomplete information, and driving work to measurable outcomes. 

• Collaboration and stakeholder-management skills across product, data science, engineering, privacy, security, and partner teams.