Microsoft Opportunities

Full Job Description

Design, build, and operate scalable data pipelines and services that ingest and unify customer support signals across channels—voice, chat, Copilot, and knowledge base—powering an AI-native support insights and analytics platform. Develop governed semantic models and Power BI datasets that shift analytics from report-heavy delivery to semantic-model-led, self-serve, AI-native insights. Build AI-native capabilities—data agents, Copilot experiences, knowledge agents, and self-serve report builders—including retrieval, orchestration, and evaluation of model quality. Ensure data quality, lineage, and governance across the golden layer so insights are trustworthy, cited, and policy-compliant. Write clean, secure, well-tested code (SQL, Python, C#); participate in code reviews; and uphold engineering excellence and coding standards. Monitor and improve the reliability, performance, and cost efficiency of pipelines and services, participating in live-site, on-call, and incident resolution as needed. Partner with product managers, applied scientists, analysts, and stakeholders to turn support KPIs (e.g., CSAT) and reporting needs into well-scoped solutions delivered incrementally within an agile team. Developing scripts and templates for automated, fault-tolerant deployment of services Increasing the footprint and scale of services through additional data centers and clusters Creates and implements code for a product, service, or feature, reusing code as applicable. Contributes to efforts to break down larger work items into smaller work items and provides estimation. Troubleshooting live site issues as part of both product development and live site rotations. Acts as a Designated Responsible Individual (DRI) working on-call to monitor system/product feature/service for degradation, downtime, or interruptions and gains approval to restore system/product/service for simple problems. Remains current in skills by investing time and effort into staying abreast of current developments that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale. Bachelor's Degree in Computer Science or related technical field AND technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Proven track record of building and shipping production software including experience and skills in cloud services using Azure, AWS or equivalent. Demonstrated ability and experience in the entire services development lifecycle: design, implementation, deployment, and live site Strong collaborator who can clearly explain work, listen to peers and customers, embodies growth mindset, and work effectively cross group and within the team. Experience developing on cloud platforms (i.e. Azure, AWS) in a continuous delivery environment. Problem solving, implementation and communication skills. Intellectual curiosity and passion for learning new technologies. Master's Degree in Computer Science or related technical field AND 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 technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. C# & JavaScript experience a plus. Coding, debugging, algorithm design, and problem-solving skills. Passion for improving software quality and engineering excellence. Experience in developing, debugging, and supporting code in object-oriented languages and database query languages. Background on services and cloud computing a plus. Prior experience building business-centric web applications and latest web development technologies Experience building AI/LLM-powered capabilities—data agents, copilots, retrieval-augmented generation, or model evaluation—and familiarity with the Model Context Protocol (MCP). Familiarity with data quality, lineage, and governance practices over large, multi-source datasets. Familiarity with CI/CD, observability, and live-site/DevOps practices. Experience with customer service and support data, or with large-scale, customer-facing data platforms. Collaboration and communication skills and a growth mindset, with genuine passion for applying AI to transform how work gets done.