Overview
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 reasoning over enterprise data, calling tools, and automating complex workflows. You'll work across the full stack (Python, Angular, C#/.NET, and SQL on Azure), pairing strong software engineering fundamentals with deep, hands-on experience in modern AI. As a senior engineer, you'll set technical direction, raise the bar on quality through eval-driven development, and mentor others while shipping production systems that increase efficiency, scalability, and accuracy.
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
- Build AI-native intelligent operations. Independently apply Artificial Intelligence (AI) tools, Large Language Models (LLMs), and generative AI practices across the software development lifecycle to automate and improve how Azure capacity is planned, deployed, and run — taking full ownership of the quality, security, and correctness of AI-assisted designs and code.
- Own architecture and design. Lead design discussions and own the architecture of solutions in a distributed system, testing design hypotheses, weighing trade-offs, and producing specifications that meet performance, scalability, resiliency, cost, and disaster-recovery requirements.
- Write and review high-quality code. Produce extensible, maintainable, well-tested, secure, and performant code, and raise the bar for the team through thoughtful, timely code reviews that coach other engineers and drive adherence to best practices.
- Drive automation and safe deployment. Champion comprehensive automation across production and deployment — targeting zero-touch where possible — and follow safe change-deployment practices, flighting, and rollback plans to minimize customer impact.
- Ensure reliability and supportability. Integrate logging, telemetry, and monitoring; act as a Designated Responsible Individual (DRI) on an on-call rotation; and lead incident retrospectives that identify root causes and prevent recurrence.
- Engineer security in apply "security as code" principles so each layer is independently secure, partner with security experts to define invariants and threat models, and ensure AI safety features are implemented for AI production systems.
- Collaborate across teams. Identify dependencies and work across partner teams to reach shared goals, ensuring end-to-end testing, performance, and escalation pathways are established before going live.
- Understand customer needs. Partner with product, program, and security stakeholders to confirm requirements, incorporate customer insights into future designs, and advocate for the security and privacy of the people who use what we build.
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#, Java, JavaScript, or Python
- OR equivalent experience.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings:
- Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
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.
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 (RAG, DAG, function/tool calling, chat-completion APIs).
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: eval harnesses, LLM-as-judge, scoring, and regression gating.
Broad Azure services experience: Azure Functions, Cosmos DB, Azure AI Search (vector), 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 move work forward together.
#azurecorejobs
Software Engineering IC4 - 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.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
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.**