Software Engineer on the Azure Capacity Infrastructure Service

• 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.

• 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., * 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.

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