Senior AI Platform Engineer

- Design and implement highly scalable platform services and shared infrastructure components to support healthcare applications and advanced AI initiatives, ensuring these foundational services adapt to increasing data volumes and user demands while maintaining performance and availability. - Develop and uphold comprehensive CI/CD pipelines that facilitate secure and automated software delivery, integrating automated testing, security checks, compliance assessments, and deployment orchestration to enhance development speed while upholding healthcare quality and security standards. - Construct and manage containerized services using industry-standard tools like Docker and Kubernetes, ensuring resilience with effective health monitoring, auto-scaling capabilities, and strategies for graceful degradation, while assuring high availability through multi-zone deployments and robust disaster recovery processes. - Implement advanced observability tools, including extensive monitoring, centralized logging, detailed metrics collection, and distributed tracing to ensure operational excellence, prompt troubleshooting, effective capacity planning, and deep insights into system behavior across complex microservices. - Design and sustain robust storage solutions and efficient data models across both relational (e.g., PostgreSQL, MySQL) and non-relational databases (e.g., MongoDB, Redis, Cassandra), ensuring data integrity, optimal query performance, and adherence to healthcare-specific data governance requirements. - Conduct thorough production troubleshooting and detailed root cause analysis to pinpoint and address system issues, implementing preventive strategies to enhance platform reliability and continually improve system stability through post-incident evaluations and actionable remediation plans. - Collaborate effectively with product engineering teams, security experts, and compliance officers to convert complex business needs into reusable, well-documented, and secure platform capabilities, fostering consistency and minimizing duplicate efforts. - Clearly document technical decisions, architectural choices, and implementation patterns using architecture decision records (ADRs), design specifications, and comprehensive runbooks to support knowledge transfer, facilitate new team member onboarding, and promote long-term system maintainability. - Ensure compliance with security and governance requirements, particularly regarding healthcare regulations such as HIPAA, ensuring that all platform systems implement appropriate access controls, encryption protocols, audit logging, and data retention policies.