DevOps Engineer
DevOps Engineer
About GW RhythmX
Our Vision: Forever change medicine by turning intelligence into impact at every point of care.
GW RhythmX uses AI to help 150+ health systems deliver the right care, at the right time, through the right clinician — reducing burden while improving outcomes. Our solutions reach 85M+ patients, including 8M U.S. military veterans, and are recognized by KLAS Research, Fierce Healthcare, and AVIA Marketplace.
As a Symphony AI portfolio company, we combine startup agility with enterprise-scale infrastructure, including:
- Longitudinal data on 300M patients
- 4.4B annual claims
- A global network of 1.8M healthcare professionals
The Role
We are building a scalable, AI-first healthcare technology platform powered by cloud-native microservices, distributed data processing pipelines, workflow orchestration, and AI-driven healthcare applications.
As a DevOps Engineer, you will help build and operate secure, reliable, and repeatable cloud-native deployments for our healthcare SaaS platform.
You will work closely with platform engineering, application development, QA, and SRE teams to improve CI/CD automation, Kubernetes deployments, infrastructure provisioning, production observability, and cloud efficiency.
This is a hands-on engineering role requiring strong fundamentals in Azure, Kubernetes, Docker, CI/CD, GitOps, and infrastructure automation. You will contribute to building reusable automation, improving deployment reliability, and reducing manual operational effort.
What You'll Own
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CI/CD, Release Engineering & GitOps
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Build and maintain CI/CD pipelines for microservices, automating build, test, container image publishing, artifact promotion, and deployment.
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Maintain Helm charts, Kubernetes manifests, and GitOps workflows using Argo CD or Flux.
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Support standardized and repeatable deployment workflows across development, QA, staging, and production environments.
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Implement deployment preflight checks, smoke tests, automated validations, and rollback procedures.
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Support Blue/Green deployment strategies, traffic cutovers, and controlled service draining.
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Maintain version-controlled release scripts, deployment artifacts, environment variables, and configuration management.
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Identify opportunities to reduce manual deployment activities and improve release efficiency.
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Cloud Infrastructure, Kubernetes & Automation
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Deploy, monitor, and troubleshoot applications running on Azure Kubernetes Service (AKS).
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Work with Kubernetes components including pods, nodes, networking, ingress, storage, and autoscaling.
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Use Terraform/OpenTofu and Infrastructure as Code (IaC) practices to provision and configure reproducible environments.
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Automate provisioning of development, QA, and production-like environments using approved synthetic or de-identified test data.
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Develop Python, Bash, or Go utilities to automate operational tasks, diagnostics, and infrastructure validation.
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Support cloud infrastructure reliability, scalability, availability, and resource optimization.
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Database Operations & Workflow Reliability
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Support PostgreSQL operations, including backup verification, restore drills, connectivity changes, monitoring, and basic performance troubleshooting.
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Assist with automated database schema migration workflows and post-deployment data validation.
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Collaborate with engineering teams to support safe database rollout and rollback procedures.
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Implement Git-backed processes to manage and validate reference data, seed data, and feature flags across environments.
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Monitor asynchronous processing, scheduled jobs, and distributed workloads involving Temporal and Kafka.
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Support safe pause, resume, and recovery of background workers during deployments and maintenance activities.
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Site Reliability Engineering & Production Operations
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Build and maintain dashboards, alerts, logs, and traces across applications, Kubernetes clusters, databases, APIs, and background jobs.
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Work with monitoring and observability tools such as Azure Monitor, Prometheus, Grafana, and OpenTelemetry.
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Participate in on-call rotations and production incident troubleshooting.
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Follow operational runbooks, escalation procedures, and incident management practices.
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Automate smoke tests, health checks, operational diagnostics, and routine recovery activities.
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Monitor deployment frequency, change failure rate, Mean Time to Recovery (MTTR), and service availability.
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Identify recurring operational issues and implement automation to reduce operational toil.
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Security Operations & Cloud Cost Optimization
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Integrate vulnerability, dependency, and container image scanning into CI/CD pipelines.
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Support vulnerability remediation and security validation across infrastructure and application deployments.
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Implement least-privilege access, secure secrets management, and Kubernetes security baselines.
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Maintain audit-friendly infrastructure changes and secure deployment practices in regulated environments.
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Implement cloud cost tagging and dashboards across environments, services, and customers.
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Monitor cloud consumption and investigate unexpected infrastructure spending.
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Identify optimization opportunities through Kubernetes workload rightsizing, autoscaling, and removal of unused resources.
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Balance cloud cost efficiency with platform reliability, performance, and security.
Required Experience
DevOps & Cloud Infrastructure (Must-Have)
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Approximately 4 years of hands-on experience in DevOps, cloud infrastructure, platform engineering, or Site Reliability Engineering.
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Practical experience with Kubernetes, Docker, Helm, Git, and Linux.
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Working experience with Microsoft Azure cloud services, preferably Azure Kubernetes Service (AKS).
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Understanding of container registries, cloud networking, storage, identity, and monitoring.
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Experience with at least one CI/CD platform such as Azure DevOps, GitHub Actions, or Jenkins.
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Understanding of cloud-native architectures and microservices deployment practices.
CI/CD, Automation & Infrastructure as Code
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Experience building and maintaining automated CI/CD pipelines.
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Working knowledge of GitOps principles and infrastructure automation.
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Familiarity with Terraform, OpenTofu, or equivalent Infrastructure as Code tools.
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Hands-on scripting experience using Python or Bash.
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Understanding of deployment strategies, release versioning, configuration management, and rollback procedures.
Kubernetes & Production Troubleshooting
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Experience deploying and troubleshooting applications in Kubernetes environments.
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Understanding of pods, deployments, services, ingress, storage, networking, and autoscaling.
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Ability to troubleshoot distributed services using logs, metrics, kubectl, Linux commands, and networking fundamentals.
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Understanding of production monitoring, application health checks, and incident troubleshooting.
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Familiarity with secure deployment practices and production change controls.
Database & Distributed Systems Fundamentals
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Basic working knowledge of PostgreSQL and database operations.
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Understanding of database backup, recovery, schema migrations, and data validation.
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Exposure to asynchronous processing, distributed workflows, and event-driven architectures.
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Understanding of operational reliability, fault tolerance, and recovery mechanisms.
Security & Operational Ownership
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Understanding of vulnerability scanning, dependency management, and container security.
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Familiarity with secrets management, access controls, and infrastructure security.
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Strong ownership and accountability when supporting production systems.
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Good documentation, communication, and troubleshooting skills.
Preferred Technical Stack Experience
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Cloud: Microsoft Azure, Azure Kubernetes Service (AKS), AWS.
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Containerization: Kubernetes, Docker, Helm.
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CI/CD: Azure DevOps, GitHub Actions, Jenkins.
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GitOps: Argo CD, Flux.
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Infrastructure as Code: Terraform, OpenTofu.
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Scripting: Python, Bash, Go.
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Databases: PostgreSQL.
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Workflow Orchestration: Temporal.
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Messaging & Distributed Systems: Kafka.
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Observability: Azure Monitor, OpenTelemetry, Prometheus, Grafana, Kubesense.
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Security: Azure Key Vault, vulnerability scanning, container security.
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Cloud Cost Management: Azure Cost Management, FinOps tagging and cost attribution.
Builder Mindset (Non-Negotiable)
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Hands-on engineering mindset with a passion for automation and problem-solving.
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Strong ownership and willingness to take responsibility for production systems.
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Comfortable diagnosing technical issues and working through ambiguity.
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Proactive approach to identifying repetitive tasks and eliminating manual operational effort.
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Strong curiosity and willingness to learn new technologies and engineering practices.
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Ability to collaborate effectively with application, platform, QA, and SRE teams.
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AI-first, AI-fast approach to engineering productivity and operational problem-solving.
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Outcome-driven mindset — focused on reliability, efficiency, and measurable impact.
What Success Looks Like
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Reliable and repeatable deployments across development, QA, staging, and production environments.
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Reduced manual intervention through CI/CD and infrastructure automation.
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Stable Kubernetes deployments and improved cloud infrastructure reliability.
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Well-maintained Helm charts, GitOps configurations, and deployment pipelines.
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Automated deployment validations, smoke tests, and rollback procedures.
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Improved observability across applications, databases, infrastructure, and distributed workflows.
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Reliable database backup, recovery, and deployment validation processes.
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Stronger security practices across infrastructure and deployment pipelines.
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Improved cloud cost visibility and resource utilization.
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Reduced operational toil and faster incident troubleshooting.
First 90 Days
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Independently support standard AKS deployments.
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Troubleshoot common Kubernetes and infrastructure issues.
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Understand existing CI/CD pipelines and maintain operational runbooks.
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Deliver meaningful automation improvements.
Within 6 Months
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Own selected CI/CD pipelines, Helm charts, and GitOps configurations.
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Implement automated release validations.
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Improve visibility into service health and cloud spending.
Within 12 Months
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Contribute to reliable multi-customer deployment workflows.
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Support tested recovery and rollback procedures.
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Reduce manual operational effort through automation.
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Demonstrate measurable improvements in operational reliability and cloud cost efficiency.
This Role Is Not For You If
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You prefer manual infrastructure management over automation.
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You are not comfortable troubleshooting Kubernetes and production infrastructure issues.
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You have experience only in monitoring without hands-on deployment and automation exposure.
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You are not interested in learning cloud-native technologies and distributed systems.
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You prefer working independently without collaborating with engineering teams.
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You are not comfortable taking ownership of production reliability and operational responsibilities.
Why Join Us
You will contribute to building the core infrastructure that powers AI-driven healthcare applications, enabling:
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Scalable and reliable cloud-native platforms.
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Automated and standardized multi-customer deployments.
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Secure and resilient healthcare technology infrastructure.
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Reliable data processing and workflow orchestration.
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Next-generation AI-powered healthcare applications.
This is an opportunity to work at the intersection of Cloud Infrastructure, Kubernetes, Platform Engineering, DevOps, SRE, and AI-driven Healthcare Technology while growing your expertise in modern cloud-native engineering.
About the Company
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