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# Senior Software Engineer

- **Company:** Microsoft
- **Location:** Redmond, WA, United States
- **Experience:** Expert
- **Salary:** $119,800.0 - $234,700.0
- **Contract:** Permanent contract
- **Skills:** AI Evaluation, C (Programming Language), Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Application Integration Architecture, Microsoft Azure, Microsoft Online Services, C Sharp (Programming Language), C++ (Programming Language), Cloud Computing, Information Leak Prevention, Distributed Systems, Python (Programming Language), Microsoft Software, OpenAI, Microsoft Copilot, Zero Trust Network Access, Search Technologies, Software Engineering, TypeScript, Azure Service Bus, Enterprise Software Applications, Computer Network Operations, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Agentic-AI, AI Platforms, Kubernetes, Infrastructure Automation Frameworks, Information Technology, AutoGen, Search Engines, Cosmos DB, Machine Learning Operations, Semantic Kernel, Human in the Loop
- **Published:** November 1, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-redmond-wa--149b5010-c1cb-4c65-9bdc-49412d40d2ae

## About the Role

Software Engineering, Microsoft Windows Azure, Microsoft Product Family, Microsoft Bing Search Engine, Sustainability, Network Operations Center, Certified Supply Chain Professional (CSCP), Supply Chain, Cloud Computing, Artificial Intelligence (AI), * Bachelors Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, 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

 * Advanced proficiency in one or more languages such as C#, Python, Java, JavaScript, or TypeScript.
 * Experience designing, delivering, and operating distributed cloud services or enterprise-scale platforms.
 * Proven experience building AI-enabled applications using LLMs, prompt engineering, embeddings, vector search, and RAG.
 * Strong understanding of system design, distributed systems, APIs, resiliency, security, and observability.
 * Practical experience with Azure OpenAI, Azure AI Foundry, Semantic Kernel, AutoGen, or similar AI platforms.
 * Experience deploying enterprise-scale copilots, AI agents, RAG platforms, or multi-agent systems into production.
 * Knowledge of AI evaluation, responsible-AI practices, content safety, and human-in-the-loop mechanisms.
 * Familiarity with Azure technologies such as AKS, App Service, Cosmos DB, Event Hubs, or Azure Monitor.
 * Expertise in Kubernetes, containers, IAC tools, private networking, and Zero Trust architecture.
 * Strong background in MLOps, experimentation, and AI telemetry with model lifecycle expertise.

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.

## Description

* Lead the design, development, and operation of complex software and AI solutions.
 * Build production-grade copilots, autonomous agents, and multi-agent workflows.
 * Create architecture patterns, frameworks, APIs, and platform capabilities for AI integration.
 * Design secure integration with enterprise applications and data sources.
 * Develop evaluation frameworks focusing on accuracy, relevance, safety, and reliability.
 * Implement observability to monitor applications, models, and agents effectively.
 * Drive architectural decisions for model selection, scalability, and optimization.
 * Apply security, privacy, and compliance controls across the engineering lifecycle.
 * Address risks like prompt injection, data leakage, and unsafe actions proactively.
 * Resolve complex production incidents and technical issues efficiently.