Director of Platform Engineering, Hippocratic AI

• 10+ years of engineering experience, including 5+ years leading infrastructure, SRE, or platform teams at scale
• Proven success in managing large-scale distributed systems and global cloud infrastructure
• Deep experience with high-performance computing or large-scale AI workloads
• Strong background in cloud platforms (AWS, GCP, Azure) and infrastructure-as-code (Terraform, Pulumi, etc.)
• Expertise in observability stacks (Prometheus, Grafana, OpenTelemetry, Datadog, etc.) and operational excellence
• Experience with security and compliance frameworks relevant to healthcare (HIPAA, SOC 2)
• Exceptional communication skills and the ability to partner across product, AI research, and operations

Desirable

• We are seeking a Director of Engineering – Platform Engineering to lead the design, implementation, and operation of HippocraticAI’s cloud infrastructure, observability systems, and GPU control plane
• This leader will be responsible for scaling our global compute fabric to support cutting-edge LLM workloads while maintaining exceptional reliability, security, and cost efficiency
• You will build and lead a multidisciplinary engineering team spanning cloud operations, SRE, and GPU orchestration, working closely with product development, AI research, and compliance to deliver world-class infrastructure for healthcare AI
• Recruit and develop a world-class platform engineering team
• Foster a culture of innovation, accountability, and technical excellence
• Mentor and coach engineers and managers to achieve high performance and career growth
• Build and scale a high-performing team responsible for all infrastructure operations and systems reliability
• Define and execute the long-term infrastructure roadmap for a multi-cloud, multi-region GPU and compute environment
• Drive excellence in cloud cost optimization, capacity planning, and service reliability
• Cloud Operations & Control Plane
• Architect and manage HippocraticAI’s global GPU control plane, enabling dynamic provisioning, scheduling, and monitoring of inference workloads across regions and providers
• Lead the design and automation of deployments (AWS, GCP, Azure, on-prem) using infrastructure-as-code and CI/CD best practices
• Ensure strong security posture and compliance across all environments, aligned with HIPAA, SOC 2, and other healthcare data standards
• Develop and scale comprehensive observability systems—covering telemetry, tracing, logging, and alerting—to ensure full visibility into production systems and AI workloads
• Establish SLOs, SLIs, and SLAs for all mission-critical services and infrastructure
• Implement robust incident management, root cause analysis, and continuous improvement processes
• Partner with AI and product teams to anticipate infrastructure needs and design scalable architectures for rapid experimentation and deployment
• Contribute to the design of internal developer platforms that improve productivity and standardization
• Evaluate emerging technologies (e.g., new GPU hardware, orchestration frameworks, data center partnerships) to advance our capabilities