Software Development Engineer II - Applied AI at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Software Development, AI Integration, Cloud Computing, Distributed Systems, MLOps, LLMOps, C, C++, C#, Java, JavaScript, Python, Monitoring, Troubleshooting, Containerization, Azure, AWS

Industry

Software Development

Description

You'll collaborate with cross-functional teams to deliver high-impact features aligned with enterprise standards and cloud-scale requirements. Design and develop highly usable, scalable application capabilities, integrating AI models and enhancing existing features to meet evolving customer needs. Build and debug production-grade code in distributed systems Troubleshoot live site issues as part of both product development and live site support rotations, ensuring rapid resolution and learning. Ensure high reliability and performance of applications and services through intelligent monitoring, alerting, and proactive failover strategies. Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python 1+ years of professional experience working with generative artificial intelligence, large language models, or agent-based systems. These requirements include but are not limited to the following specialized security screenings: Master's Degree in Computer Science or related technical field AND 3+ 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 5+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. AI & Domain Expertise: Deep expertise in one or more AI domains, with a proven track record of deploying and scaling AI models in cloud environments. MLOps & LLMOps: Strong experience with MLOps workflows (CI/CD, monitoring, retraining pipelines) and familiarity with modern LLMOps frameworks. Cloud & Infrastructure: Skilled in building and operating infrastructure using Azure, AWS, or Google Cloud, and deploying containerized models with Docker, Kubernetes, or similar tools. Experience with customers success, zero trust security and compliance

Responsibilities

Collaborate with cross-functional teams to deliver high-impact features and develop scalable application capabilities. Troubleshoot live site issues and ensure high reliability and performance of applications.