Full-Time Infrastructure Engineer

• Architect, deploy, and manage Kubernetes clusters running in customer cloud tenancies (AWS, Azure, GCP).
• Create robust infrastructure-as-code templates (e.g., Terraform, Helm) for repeatable deployments.
• Implement scaling, monitoring, disaster recovery strategies, and observability solutions for proactive infrastructure management.
• Automate deployment processes for data pipelines, ML models, and analytics applications - including automated testing - to improve release velocity and stability.
• Manage containerization and orchestration of data services and workloads using Docker and Kubernetes.
• Troubleshoot performance and reliability issues across environments.
• Evaluate and recommend infrastructure solutions by conducting cost-benefit analyses comparing open source vs. cloud-native alternatives.
• Implement and maintain security controls aligned with HIPAA and HITRUST frameworks.
• Partner with compliance teams to ensure infrastructure supports ongoing certification and audit requirements.
• Configure secure networking, identity and access management (IAM), encryption (in transit and at rest), and audit logging.

• Build infrastructure to host both in-house AI models and integrate with external AI services (e.g., GPT-5 via OpenAI APIs).
• Optimize data pipelines and storage for AI training and inference workloads.
• Support GPU-based compute environments for ML workloads when required.
• Design and manage scalable API gateways and authentication mechanisms for external data consumers.
• Ensure API infrastructure can handle high-throughput, low-latency access to sensitive healthcare datasets.
• Collaborate with the data/applications team to develop and optimize data processing pipelines, using data orchestration tools like Prefect or cloud-native solutions, and support diverse client integrations (Python, R, SQL, BI tools, etc.).

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