Description:
We are looking for an AI architect senior Python & AI resource to enhance, debug, and support our production AI applications. This person will work across backend services, LLM-driven workflows, and cloud infrastructure to deliver reliable, scalable, and secure solutions.
Hybrid (Twice in a week) for local candidates. Remote can be accepted.
Key Responsibilities
Design, develop, and enhance Java-based backend services for 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 reliability, performance, and observability (logging, tracing, metrics, alerting).
Build and optimize LLM/GenAI integrations (prompt orchestration, response quality, cost/performance trade-offs).
Implement robust testing (unit, integration, regression) and ensure code quality through reviews and standards.
Collaborate with business, product, and operations teams to prioritize enhancements and fixes.
Support CI/CD pipelines, release processes, and environment stability.
Document architecture, troubleshooting guides, and production runbooks.
Mentor junior developers and drive engineering best practices.
Hands-on experience building and supporting production-grade APIs/microservices (e.g., FastAPI/Flask).
Experience with AI/LLM-based applications (prompt design, orchestration frameworks, model integration).
Strong debugging skills in distributed systems and asynchronous workloads.
Experience with cloud platforms (preferably Azure) and containerized deployments (Docker/Kubernetes).
Strong knowledge of SQL/NoSQL data handling and API integration patterns.
Familiarity with observability tools (structured logs, tracing, monitoring dashboards, alerts).
Experience with automated testing frameworks and CI/CD workflows.
Excellent communication skills and ability to work in a support-heavy, fast-moving environment.
Preferred Qualifications
Python is good to have
Experience in underwriting/insurance, document extraction, or NLP pipelines.
Exposure to vector search, RAG, semantic retrieval, and model evaluation.
Experience with secure coding, data privacy controls, and compliance-driven systems.
Prior on-call/production support ownership in enterprise systems.