Application Developer; Credit Risk & ML Platform

Location:
Remote

In person interview in Irving, TX

• Design, develop, and maintain scalable Java and Python applications supporting credit risk decisioning and machine learning model services.
• Develop high-performance REST APIs, microservices, and distributed services for real-time credit decisioning and ML model execution.
• Work extensively with Amazon Sage Maker and MLOps, including model integration, deployment, versioning, monitoring, and lifecycle management.
• Build and maintain data-driven applications using Snowflake, SQL, and large-scale credit/decisioning datasets.
• Develop and deploy cloud-native applications on AWS and Open Shift/Kubernetes, focusing on scalability, resiliency, security, and low latency.
• Collaborate with data scientists and ML engineers to product ionize machine learning models and integrate them into credit decisioning workflows.
• Implement automated testing, CI/CD, and engineering practices using Git Hub Actions, Terraform, and modern development workflows.
• Monitor and troubleshoot applications using Kibana/Elastic telemetry, logs, metrics, and distributed tracing to identify performance and production issues.
• Use Claude Code, OpenAI Codex, and Cursor to improve development productivity, code quality, testing, documentation, and troubleshooting.
• Contribute to system architecture, performance optimization, reliability, security, and continuous improvement of business-critical credit risk and ML platforms.