Microsoft AI Software Engineer 

United States, Washington 

734882018

As an AI Software Engineer, you would implement architectural changes and influence roadmap of relevant software and platform components to enable AI Solutions and Product Integration for MCAPS Businesses. You will also play a pivotal role in designing, implementing, and maintaining robust data acquisition and metadata-driven orchestration pipelines.

Required Qualifications:

• 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
  • OR equivalent experience.

Preferred Qualifications:

• 2+ years of experience in Platform and Product Engineering, API Development and Data Engineering.
• Proficient in C#, Python, and SQL.
• Expertise in developing transformation logic using Pyspark and Spark SQL in Azure Databricks and Azure Synapse.
• Knowledge of LLMs including Microsoft Azure Open AI products and services (AOAI Studio, Copilot Studio etc).
• Proven experience in building acquisition and metadata-driven orchestration pipelines using Azure Data Factory.
• Effective communication and collaboration skills.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until August 5, 2024.

The Artificial Intelligence (AI) Software Engineer will be responsible for:

• Collaborate with AI & data scientists to design sophisticated AI models leveraging first party products and platforms.
• Partner with first party product and platform teams to build key capabilities that can be leveraged to create AI Skills, Plugins and Copilot experiences.
• Optimize AI model performance, scalability, and efficiency.
• Stay up to date with the latest advancements AI Platforms, Products and Libraries.
• Ramp up on latest deep learning model architectures/algorithms, Open AI enhancements and large language models (LLM) directions.
• Develop and maintain data acquisition pipelines using Azure Data Factory.
• Implement metadata-driven orchestration pipelines to ensure scalability and flexibility.
• Develop complex transformation logic in Azure Databricks.
• Collaborate with cross-functional teams to understand data requirements and implement solutions accordingly.
• Optimize and troubleshoot existing data pipelines for performance and reliability.
• Implement best practices for data quality, security, and compliance.

• Embody our and .