Role Description Come help us build the world's computer. Azure's hyperscale growth continues and is only increasing, and the intelligence behind that growth is being written right now, by us. You'll join a team that sits at the intersection of massive distributed systems and cutting-edge Artificial Intelligence (AI), where the decisions our software makes directly shape Microsoft's capacity, efficiency, and profitability across the planet. If you want your code to move the needle at true hyperscale, this is where you do it. As a Senior Software Engineer on the Azure Capacity Infrastructure Service, you'll design and build the intelligent operations that orchestrate Azure's datacenter buildout with minimal customer disruption and maximum efficiency. You'll apply Artificial Intelligence (AI) and Large Language Models (LLMs) across the software development lifecycle to reason over complex, real-time signals, safely planning, deploying, and running the systems that expand Azure's global footprint. This opportunity will allow you to deepen your expertise in applied AI and distributed systems, grow your technical leadership and influence across engineering teams, and shape the architecture of a service that operates at a scale few engineers ever touch. In this role, you'll: - Design, build, deploy, and run AI agent systems and LLM-powered applications that bring intelligence to this distributed platform. - Work across the full stack (Python, Angular, C#/.NET, and SQL on Azure). - Set technical direction, raise the bar on quality through eval-driven development, and mentor others. Responsibilities - Build AI-native intelligent operations by applying AI tools, LLMs, and generative AI practices across the software development lifecycle. - Own architecture and design by leading discussions and producing specifications that meet performance, scalability, resiliency, cost, and disaster-recovery requirements. - Write and review high-quality code that is extensible, maintainable, well-tested, secure, and performant. - Drive automation and safe deployment, targeting zero-touch where possible. - Ensure reliability and supportability through logging, telemetry, and monitoring. - Engineer security by applying "security as code" principles and partnering with security experts. - Collaborate across teams to identify dependencies and ensure end-to-end testing. - Understand customer needs by partnering with stakeholders to confirm requirements and advocate for security and privacy. 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#, Java, JavaScript, or Python OR equivalent experience. - Ability to meet Microsoft, customer and/or government security screening requirements. 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 OR equivalent experience. - Proven experience as a full-stack developer with strong expertise in Angular (TS), Python, C#/.NET 8, and SQL. - Demonstrated experience building AI agent systems and LLM applications. - Hands-on knowledge of RAG technologies—vector search and knowledge graphs. - Experience building and calling MCPs. - Proven expertise in Microsoft Azure cloud architecture, deployment, and management. - NL-to-SQL experience—prompts, few-shot/context corpus, table rules, tools, and eval accuracy. - AI eval-driven development and LLM harness design. - Broad Azure services experience: Azure Functions, Cosmos DB, Azure AI Search, Blob Storage, Web PubSub / SignalR, Kusto, Fabric SQL, and Lakehouse. - Ability to own and ship significant features or architectural components end to end. - Collaboration across teams: experience aligning with partners and moving work forward together. Compensation The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year. Company Description Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

• Assist development teams with support activities for the z/OS operating system; support for z/OS utilities; performance analysis of applications in the z/OS environment; and work with DevOps technologies and tools • Programming knowledge in Enterprise COBOL 4.0 or higher • Work with CICS configurations and definitions • Perform business modeling in CA‑GEn 8 or higher.

• Assist development teams with support activities for the z/OS operating system; • Support for z/OS utilities; • Analyze application performance in the z/OS environment and work with technologies and tools for DevOps;

Role Description As an RL Environment Software Engineer, you will sit at the intersection of research engineering and traditional software engineering, building the environments that simulate real-world workflows and the agents that automate them. This is forward-looking work, you will help research and predict what high-quality environments the frontier will need next, then build them from the ground up. You will join a brand-new RL team being assembled with exceptional talent, with a clear path to grow alongside it as the function scales into industry pods. Responsibilities - Design and build high-quality RL environments that simulate real working environments end to end. - Develop agents for the tasks within those environments and iterate until they are efficient and production-ready. - Partner with the research team to scope which environments to build and why, staying ahead of future demand rather than only meeting present needs. - Own the backend and infrastructure layers that make environments reliable and scalable. - Help set engineering standards for a zero-to-one team as the RL function grows. Qualifications - Strong machine-learning engineers who code heavily and build systems from scratch, with strong intuition for reinforcement learning. - Proficiency across a modern stack, Node.js and Python on the backend and React/TypeScript on the frontend, with strong Kubernetes and Docker skills. - Comfort operating in a fast-paced startup environment with high ownership and long hours. - A track record of meaningful tenure and impact at previous companies. - Reinforcement-learning experience or an RL research background is a strong plus, though not required. - Bachelor's degree in computer science or a related technical field, or equivalent practical experience. Requirements - Compensation: $180K-$220K base, ~$400K+ OTE (uncapped profit share) Company Description Our partner is a fast-growing applied AI research lab that builds high-quality reinforcement-learning environments and agents sold to the world's leading AI labs. In under two years they have scaled to a nine-figure revenue run rate and grown their team severalfold in a matter of months, backed by leading venture investors. Quality is their core differentiator, and they are rapidly expanding into new domains.