Ai Applications Engineer

AI Applications Engineer Overview

• The AI Applications Engineer will design and implement AI-powered solutions to enhance workflows within a professional services environment.
• Collaborate with stakeholders to translate complex needs into scalable and secure AI applications.
• Develop generative AI applications utilizing cutting-edge technologies like large language models and retrieval-augmented generation.
• Work in a hybrid or remote capacity, ensuring flexibility and adaptability in a dynamic environment.
• Leverage cloud services and APIs to integrate advanced AI functionalities into existing systems.
• Contribute to the development of secure and reliable applications handling sensitive data.
• Stay updated on advancements in AI technologies and apply them to improve operational efficiency.
• Provide training and support to staff on the effective utilization of AI tools.

AI Applications Engineer Key Responsibilities & Duties

• Design, develop, test, and maintain AI-driven web applications using JavaScript, .NET, and Python.
• Optimize prompts and model outputs for large language model applications, ensuring high-quality results.
• Integrate APIs and services like Anthropic Claude and Azure AI Foundry into firm applications.
• Apply retrieval-augmented generation techniques to enhance AI-generated outputs.
• Build and support data-driven tools and dashboards integrated with Azure SQL and Microsoft Graph.
• Implement security practices for applications and data flows, handling sensitive information securely.
• Collaborate with legal and business stakeholders to define technical requirements and deliver solutions.
• Create and maintain technical and user-facing documentation for developed applications.

AI Applications Engineer Job Requirements

• Bachelor’s degree in Computer Science, Information Systems, or related field preferred.
• Minimum of three years of experience in web application development using JavaScript, .NET, and Python.
• Hands-on experience with generative AI applications, including RAG and prompt engineering.
• Proficiency with Azure cloud services and on-premises deployment; Microsoft Graph experience is advantageous.
• Strong analytical troubleshooting skills across technical disciplines and areas.
• Proficiency in Git and collaborative development practices.
• Ability to communicate technical information clearly to non-technical audiences.
• Detail-oriented with strong organizational and time-management skills in a fast-paced environment.