AI Engineer - Production Applications

Role Overview

Production Ownership and Development

• Own AI applications after deployment and drive application issues, bugs, and user-reported problems through resolution.
• Use logs, monitoring tools, and diagnostic information to identify root causes and improve reliability.
• Coordinate with internal development teams and external vendors when issues need broader technical involvement.
• Provide business-hours production support for the AI application portfolio.
• Troubleshoot, modify, and enhance existing AI applications using Python and TypeScript.
• Deliver smaller features and application improvements based on business-user feedback; test and validate enhancements before release.
• Work with APIs, cloud services, and existing application components to diagnose and resolve issues.

Support Automation and User Engagement

• Identify recurring support issues that can be reduced or eliminated through automation.
• Build or enhance AI agents and workflows to monitor applications and provide diagnostic information when problems occur.
• Where appropriate guardrails exist, contribute to solutions that recommend or automate repeatable corrective actions.
• Engage non-technical users, translate business problems and feedback into technical solutions, and demonstrate completed changes.
• Maintain a service-oriented experience while retaining ownership of technical issues.

Technical Experience

• 2+ years developing, enhancing, and supporting Generative AI or LLM-enabled applications.
• 5+ years of software engineering experience with Python and TypeScript.
• 3+ years owning or supporting production applications, including investigating user-reported issues and using logs and monitoring tools to find root causes.
• 5+ years of practical experience with applications in Microsoft Azure.
• Experience with APIs, modern cloud-based application architectures, and existing application enhancements.
• Experience in one or more areas such as RAG, enterprise search, copilots or chatbots, document processing, LLM applications, or AI agents and workflows.
• Specific LLM or agent frameworks are not required.

Problem Solving and Communication

• Strong troubleshooting and root-cause analysis skills, with the ability to move between code, logs, user-reported behavior, and implementation.
• Proactive approach to identifying repetitive issues and opportunities for automation.
• Ownership mindset, taking issues from initial investigation through resolution.
• Strong verbal and written communication; comfortable working with business users and non-technical stakeholders.
• Able to translate feedback into technical requirements, demonstrate completed changes, and explain solutions clearly.
• Able to balance immediate issue resolution with longer-term automation and improvement.

About Affinity