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Design, build, and maintain full‑stack features for a clinical SaaS platform. Drive architecture, collaborate with product, ML, infra, and regulatory teams, uphold engineering standards, mentor peers, and ensure reliability, data integrity, and compliance for clinical trial workflows.

Design and scale machine learning infrastructure across AWS and on-premises environments. Lead MLOps architecture, automation, CI/CD, deployment, monitoring, and reproducible ML workflows using Kubernetes, Airflow, and related tools. Collaborate with engineering and data science teams, evaluate MLOps technologies, ensure security and compliance, conduct design reviews, enforce engineering standards, and mentor junior engineers.

Build and maintain automated UI, API, and integration test suites; contribute to test strategies, code reviews, debugging, manual testing, CI/CD pipelines, and documentation. Help manage AWS and Kubernetes test infrastructure, improve test reliability, and investigate failures across software, data, and infrastructure layers. Collaborate with engineering, product, QA, and business teams in a distributed healthcare technology environment.

Designs, builds, and maintains backend APIs and data pipelines supporting clinical workflows and real-time data exchange. Drives platform architecture, code quality, testing, reliability, data integrity, compliance, and inspection readiness. Collaborates with product, design, machine learning, infrastructure, clinical, QA, and regulatory teams while mentoring engineers and contributing to a SaaS healthcare platform.