DevOps Engineer

Posted 3 Days Ago
New York City, NY, USA
In-Office
180K-240K Annually
Senior level
Artificial Intelligence • Healthtech
The Role
Own and scale HIPAA-compliant AWS infrastructure and Kubernetes production clusters. Build IaC with Terraform, GitOps with Argo CD, CI/CD pipelines, observability (Prometheus/Grafana/CloudWatch), and secure networking. Support AI/ML and LLM inference workloads, automate operations with Bash/Python, and maintain reliability, security, and compliance for a mission-critical healthcare platform.
Summary Generated by Built In
DevOps Engineer

Where Medicine Meets Intelligence

Doctronic is the first AI legally authorized to practice medicine. We're processing millions of consultations monthly with 99%+ treatment plan accuracy validated by board-certified clinicians.

About the Role

We're looking for a DevOps Engineer to own our infrastructure. We're HIPAA-compliant and SOC 2 Type II certified — you'll maintain and strengthen that foundation as we scale to serve millions of patients and enterprise partners.

This role is critical to our mission. When healthcare consultations depend on your infrastructure, reliability isn't just best practice — it's a sacred responsibility. You'll combine hands-on technical work with strategic infrastructure leadership, ensuring Doctronic remains the most trusted AI diagnostic platform in healthcare.

What You'll Build

Cloud Infrastructure

  • Design, deploy, and maintain AWS infrastructure using ECS and core AWS services, including EC2, IAM, VPC, ALB/NLB, CloudWatch, ECR, S3, RDS, Glue.

  • Operate and scale production Kubernetes clusters with Helm-based application deployments.

  • Implement GitOps workflows with Argo CD to enable secure, automated, and auditable releases.

Infrastructure as Code & CI/CD

  • Provision and manage cloud infrastructure using Terraform.

  • Build and optimize CI/CD pipelines with GitHub Actions, GitLab CI, or similar platforms.

  • Automate infrastructure and operational workflows to improve reliability and reduce manual effort.

AI/ML & LLM Infrastructure

  • Deploy, maintain, and optimize infrastructure for AI/ML services and Large Language Models (LLMs).

  • Support scalable inference workloads with a focus on performance, reliability, and cost efficiency.

  • Collaborate with engineering teams to deliver production-ready AI platforms.

Networking & Security

  • Design and manage cloud networking, including VPCs, VPNs, Load Balancers, DNS, routing, and secure connectivity.

  • Integrate SIEM solutions to improve infrastructure visibility and incident response.

  • Implement security best practices, identity management, and least-privilege access across cloud environments.

Observability & Reliability

  • Build monitoring, logging, and alerting solutions using Prometheus, Grafana, CloudWatch.

  • Improve platform reliability through proactive monitoring, incident response, and performance optimization.

  • Build and optimize containerized workloads using Docker.

  • Administer Linux-based production environments.

  • Automate operational tasks and infrastructure management using Bash and Python.

Who You Are

  • 5+ years of experience as a DevOps Engineer or Site Reliability Engineer.

  • Strong hands-on experience with AWS, Kubernetes, Terraform, Docker, Helm, and Argo CD.

  • Proven experience designing and operating highly available, cloud-native production infrastructure.

  • Solid understanding of Linux administration, networking, cloud security, and Infrastructure as Code principles.

  • Experience building and maintaining CI/CD pipelines and deployment automation.

  • Familiarity with monitoring, logging, and observability platforms.

  • Experience supporting AI/ML workloads or modern distributed systems is a strong advantage.

  • Strong problem-solving skills with the ability to troubleshoot complex production environments.

  • Comfortable working in cross-functional teams and collaborating closely with software engineers, security teams, and product stakeholders.

  • Passionate about automation, reliability, scalability, and operational excellence.

Nice to Have

  • Experience with GPU infrastructure and AI/ML model deployment.

  • Familiarity with DevSecOps practices, vulnerability management, and compliance frameworks.

  • Experience with multi-cluster Kubernetes environments.

  • Knowledge of performance tuning, autoscaling, and cost optimization in AWS.

  • Experience supporting high-traffic, mission-critical production systems.

  • Understanding of disaster recovery, backup strategies, and business continuity planning.

  • Experience working in fast-paced startup or scale-up environments.

Compensation & Benefits

Base Salary: $180K-$240K + Equity

New York City | On-site

Join our NYC team and work directly with engineering and product teams to build security into everything we do.

Equity Opportunities

Share in Doctronic's growth as we transform healthcare with AI.

Comprehensive Health Benefits

We offer comprehensive health, dental, and vision coverage—plus mental health support and flexible time off—because caring for others starts with caring for ourselves.

Building AI That Matters

Join Doctronic and work with cutting-edge AI that's transforming healthcare and helping people make faster, smarter decisions.

Reports To

Director of Engineering

Skills Required

  • 5+ years of experience as a DevOps Engineer or Site Reliability Engineer
  • Hands-on experience with AWS (ECS, EC2, IAM, VPC, ALB/NLB, CloudWatch, ECR, S3, RDS, Glue)
  • Experience operating and scaling Kubernetes production clusters
  • Proficiency with Infrastructure as Code using Terraform
  • Experience with GitOps and Argo CD
  • CI/CD pipeline experience (GitHub Actions, GitLab CI, or similar)
  • Containerization with Docker and Helm-based deployments
  • Strong Linux administration, networking, and cloud security knowledge
  • Monitoring and observability experience (Prometheus, Grafana, CloudWatch)
  • Automation and scripting experience using Bash and Python
  • Experience supporting AI/ML or LLM infrastructure and inference workloads
  • Familiarity with GPU infrastructure, multi-cluster Kubernetes, and DevSecOps practices
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The Company
HQ: New York, NY
22 Employees
Year Founded: 2023

What We Do

With over 10 million AI-doctor visits, drawing on the latest in modern medicine, we are bringing best-in-class primary care to anyone with an internet connection. Backed by Union Square Ventures, Tusk Venture Partners, and HF0.

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