Senior DevOps Engineer

About The Company VI is the market leading Enterprise-AI platform for health, serving the world’s largest health organizations — from Fortune 500 health providers to pharma and consumer brands - helping them maximize acquisition, enrollment, engagement, retention, and health outcomes. Vi offers 3 main product lines: Activate, Engage and Operate. Backed by $150M, our platform serves over 195 million members daily across Activate, Engage, Operate, and Pulse. We are based in New York, Austin, Boston, and Tel Aviv. About The Position We are seeking a highly skilled DevOps / Platform Engineer to join our R&D team. In this role, you will be responsible for designing, operating, and scaling our cloud infrastructure while supporting both engineering and machine learning initiatives. You will own our AWS environment end-to-end — from infrastructure architecture and Kubernetes operations to MLOps enablement, security hardening, and cost optimization. This role goes beyond traditional DevOps and includes responsibilities across IT operations support, multi-account AWS management, DevSecOps practices, DevFinOps ownership, and machine learning infrastructure. You will play a critical role in ensuring our systems are secure, scalable, observable, and cost-efficient, while enabling fast and reliable software and model delivery.

Requirements: • ~5 years of experience working in a DevOps or Platform Engineering role. • BSc degree in Computer Science, Engineering, or equivalent (required). • Strong hands-on experience operating in an AWS environment. • Solid understanding of networking fundamentals , including: VPC design, subnets, routing tables, Load balancers, NAT/Internet gateways. • Experience maintaining Kubernetes clusters at scale , including managing and deploying Helm charts. • Strong background in observability and monitoring using: Prometheus , Grafana , and Loki and CloudWatch. • Experience with GitOps workflows and continuous delivery using ArgoCD. • Proficiency with Infrastructure as Code (Terraform / Cloudformation), preferably using AWS CDK (Python and/or TypeScript). • Core understanding of MLOps principles , including model deployment, monitoring, versioning, and lifecycle management.