Suki builds ambient AI that drafts clinical documentation and supports coding accuracy for health systems. Its stack runs across AWS, GCP and Azure with Kubernetes and Terraform, alongside PyTorch, JAX, Llama and GPT, which points to in-house model work rather than a thin API wrapper. Accelerating, senior-weighted engineering hiring centers on multi-cloud security and AI/ML test frameworks, signaling a push to harden the platform for healthcare-grade compliance.
Suki is a Redwood City, California company founded in 2017 that develops voice-driven clinical intelligence software for healthcare providers. Its product captures clinical encounters to reduce documentation work, improve billing and coding accuracy, and surface insights for clinicians during care. The company sells to health systems and integrates with major electronic health record platforms. Suki is privately held, employs 201–500 people, and hires in the United States and India.
Suki runs on AWS, GCP and Azure with Kubernetes, Terraform and Kafka, builds in Go, Python, C++ and Java, and uses PyTorch, JAX, Transformers, Llama, GPT and Vertex AI for ML work.
Yes. Engineering leads Suki's accelerating hiring, weighted toward senior roles, with additional openings in product, support, design, legal, marketing, ops and sales across the United States and India.
Job posts point to multi-cloud security architecture, IaC security in CI/CD, Kubernetes cluster security, AI/ML platform stress testing and test frameworks, plus a sales onboarding program.
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Suki's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
