Job Description Help for Job Description. Opens a new window. The AI Software Engineer is responsible for designing, developing, operating, and continuously improving AI-enabled business applications while helping transform software delivery practices through agent-assisted and agent-driven engineering models. Working as part of an engineering transformation team, this role combines software development, AI implementation, cloud engineering, and process modernization. Team members are expected not only to deliver production-grade solutions, but also to challenge and improve how software is designed, developed, tested, deployed, documented, and supported. This team serves as both the delivery organization for a portfolio of enterprise AI applications and the proving ground for a next-generation software development lifecycle.

RESPONSIBILITIES

• Application Engineering & Product Ownership
• Design, develop, test, deploy, and support AI-enabled business applications.
• Enhance and maintain existing enterprise AI applications and services.
• Implement new features, integrations, and automation capabilities.
• Collaborate with product owners and stakeholders.
• Contribute to modernization of enterprise application platforms.
• Agentic Engineering & SDLC Transformation
• Analyze existing SDLC workflows for agent-assisted execution.
• Design and implement agentic workflows.
• Build reusable agents, prompts, workflows, and automation components.
• Measure improvements in engineering effectiveness.
• Help establish repeatable engineering patterns.
• Contribute to an agentic-first engineering operating model.
• AI Solution Development
• Implement agent-based systems, workflow orchestration, harness like components, and document intelligence capabilities.
• Develop integrations with approved AI platforms and enterprise data sources.
• Optimize solutions for performance, reliability, and cost.
• Cloud & Platform Engineering
• Develop cloud-native Azure solutions.
• Build APIs and integration services.
• Implement observability and monitoring.
• Support production deployments and operations.
• Engineering Excellence
• Develop high-quality maintainable software.
• Participate in code reviews and design reviews.
• Contribute to testing and quality processes.
• Improve productivity through automation and tooling.
• Governance, Security & Compliance
• Ensure compliance with enterprise security, privacy, Responsible AI, and regulatory requirements.
• Implement auditing, monitoring, and traceability controls.
• Collaboration & Continuous Improvement
• Collaborate across product, architecture, platform, security, and governance teams.
• Support agile delivery and continuous learning.
• Drive measurable improvements in engineering effectiveness.