Job Summary
We are seeking an experienced AI Architect Lead Advisor to enhance, debug, and support production AI applications. The ideal candidate will work across backend services, LLM-driven workflows, and cloud infrastructure to deliver reliable, scalable, secure, and production-ready AI solutions.

Key Responsibilities
• Design, develop, and enhance Java-based backend services supporting AI/ML workflows.
• Troubleshoot and debug complex issues across application, integration, and production environments.
• Own production support activities, including incident response, root cause analysis, and post-incident improvements.
• Improve application reliability, performance, and observability through logging, tracing, metrics, and alerting.
• Build and optimize LLM and Generative AI integrations, including prompt orchestration and response quality optimization.
• Evaluate and optimize AI solutions for performance, reliability, and cost.
• Implement unit, integration, and regression testing to maintain application quality.
• Conduct code reviews and establish engineering standards and best practices.
• Collaborate with business, product, and operations teams to prioritize enhancements and issue resolution.
• Support CI/CD pipelines, release processes, and environment stability.
• Develop and maintain architecture documentation, troubleshooting guides, and production runbooks.
• Mentor junior developers and promote engineering best practices.
• Build and support production-grade APIs and microservices.
• Support cloud-based and containerized application deployments.

Required Qualifications
• Strong experience designing and supporting production AI/ML applications.
• Hands-on experience developing production-grade APIs and microservices.
• Experience with Java-based backend development.
• Experience with AI and LLM-based applications, including prompt design, orchestration frameworks, and model integrations.
• Strong debugging and troubleshooting skills across distributed systems and asynchronous workloads.
• Experience with cloud platforms, preferably Microsoft Azure.
• Experience with Docker and Kubernetes.
• Strong knowledge of SQL and NoSQL data handling.
• Experience with enterprise API integration patterns.
• Experience with observability practices, including structured logging, tracing, monitoring dashboards, metrics, and alerts.
• Experience with automated testing frameworks and CI/CD workflows.
• Experience supporting production applications and resolving complex technical issues.
• Excellent communication, collaboration, and technical leadership skills.
• Ability to work effectively in a fast-paced, production support-oriented environment.

Preferred Qualifications
• Python development experience.
• Experience in underwriting, insurance, document extraction, or NLP pipelines.
• Experience with vector search, Retrieval-Augmented Generation (RAG), semantic retrieval, and model evaluation.
• Experience with secure coding practices, data privacy controls, and compliance-driven systems.
• Previous experience owning on-call or production support activities for enterprise systems.