Ai Solutions Engineer

AI Solutions Engineer Overview

• The AI Solutions Engineer will design, build, and deploy custom applications and AI solutions for business professionals and practice groups.
• Collaborate with stakeholders to identify automation opportunities and deliver iterative solutions enhancing business processes and capabilities.
• Utilize modern software development practices to create applications on the Microsoft and Azure stack, ensuring compliance with security standards.
• Develop AI solutions, including retrieval-augmented generation assistants and integrations with enterprise AI platforms.
• Employ CI/CD pipelines for automated build, test, security scanning, and deployment of applications and services.
• Leverage AI-assisted engineering tools to accelerate development while maintaining code quality and security.
• Monitor and evaluate deployed applications, ensuring scalability, reliability, and performance over time.
• Stay updated on emerging AI technologies and recommend adoption strategies to improve outcomes.

AI Solutions Engineer Key Responsibilities & Duties

• Design, build, test, deploy, and support custom web applications and APIs for business professionals and practice groups.
• Collaborate with network systems and information security teams to ensure solutions comply with governance standards.
• Develop and maintain REST APIs and production data pipelines using sound SQL and data modeling practices.
• Integrate enterprise AI platforms through APIs and SDKs, building agentic solutions with frameworks and services.
• Operate applications and services on Azure, utilizing serverless compute and managed databases.
• Follow established software development life cycle methodologies, including Git-based source control and peer code review.
• Evaluate and maintain deployed AI solutions, tracking quality metrics such as accuracy, latency, and scalability.
• Contribute to team standards and reusable components, ensuring maintainability and security of all code produced.

AI Solutions Engineer Job Requirements

• Bachelor of Science (BS) degree in a relevant field is required.
• 5+ years of professional software engineering experience with C#, ASP.NET MVC, React, and Python.
• 2+ years of experience shipping LLM-based applications to production environments.
• Proficiency in SQL and data modeling, including production pipelines on SQL Server or similar platforms.
• Experience deploying services on Azure or AWS, including containers and serverless computing.
• Knowledge of CI/CD pipelines and Git-based workflows is essential.
• Preferred experience in regulated industries such as legal or financial services.
• Familiarity with AI coding assistants and frameworks for professional development.