Azure AI Engineer

Leidos

2d•Remote

About The Position

The Leidos Digital Modernization Sector is seeking an experienced Azure AI Software Engineer which allows for full time telework from any U.S. based location. POSITION SUMMARY: We are seeking an experienced Azure AI Software Engineer to design, develop, and deploy intelligent automation solutions leveraging Microsoft Azure. The ideal candidate will be Azure certified, have several years of hands-on Azure experience, and a strong background in automating business processes using Robotic Process Automation (RPA) tools.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, Data Science, Information Systems, or related technical discipline (or equivalent professional work experience).
Azure AI Engineer Associate (AI-102) or similar Azure certification.
4+ years of hands-on experience with Microsoft Azure cloud services.
Experience designing and implementing RPA solutions (e.g., Automation Anywhere, UiPath, Power Automate).
Proficiency in Python, C#, or other relevant programming languages.
Experience with data modeling, ETL pipelines, and API integration.
Strong understanding of cloud computing, data management, and automation best practices.
Excellent communication and documentation skills.
Must be a U.S. Citizen and able to obtain and maintain a security clearance.

Nice To Haves

Familiarity with automation platforms (RPA, workflow, or AI orchestration).
Experience quantifying and modeling ROI for automation projects.
Experience with data science, intelligent document processing, agentic AI and machine learning techniques.
Familiarity with MLOps practices and deploying models into production.
Experience with data visualization and BI tools (e.g., Power BI).
Master’s degree in a related discipline.

Responsibilities

Design, build, and test AI-driven automation workflows using Azure services and RPA platforms.
Integrate automation solutions with enterprise systems, APIs, and data sources.
Collaborate with stakeholders to map processes and define automation logic.
Implement monitoring, logging, and exception handling for automated workflows.
Optimize automation performance and reliability.
Document automation designs and operational procedures.
Support change management and user enablement for automated processes.
Apply software engineering best practices (version control, CI/CD, testing, documentation) to all projects.
Peer review code written by fellow team members.