DevOps Engineer
Confirmed on the employer's own hiring board on Nov 7, 2026. First seen by Alion on Nov 6, 2026.
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
CI/CD, Release Engineering & GitOps
Build and maintain CI/CD pipelines for microservices, automating build, test, container image publishing, artifact promotion, and deployment.
Maintain Helm charts, Kubernetes manifests, and GitOps workflows using Argo CD or Flux.
Support standardized and repeatable deployment workflows across development, QA, staging, and production environments.
Implement deployment preflight checks, smoke tests, automated validations, and rollback procedures.
Support Blue/Green deployment strategies, traffic cutovers, and controlled service draining.
Maintain version-controlled release scripts, deployment artifacts, environment variables, and configuration management.
Identify opportunities to reduce manual deployment activities and improve release efficiency.
Cloud Infrastructure, Kubernetes & Automation
Deploy, monitor, and troubleshoot applications running on Azure Kubernetes Service (AKS).
Work with Kubernetes components including pods, nodes, networking, ingress, storage, and autoscaling.
Use Terraform/OpenTofu and Infrastructure as Code (IaC) practices to provision and configure reproducible environments.
Automate provisioning of development, QA, and production-like environments using approved synthetic or de-identified test data.
Develop Python, Bash, or Go utilities to automate operational tasks, diagnostics, and infrastructure validation.
Support cloud infrastructure reliability, scalability, availability, and resource optimization.
Database Operations & Workflow Reliability
Support PostgreSQL operations, including backup verification, restore drills, connectivity changes, monitoring, and basic performance troubleshooting.
Assist with automated database schema migration workflows and post-deployment data validation.
Collaborate with engineering teams to support safe database rollout and rollback procedures.
Implement Git-backed processes to manage and validate reference data, seed data, and feature flags across environments.
Monitor asynchronous processing, scheduled jobs, and distributed workloads involving Temporal and Kafka.
Support safe pause, resume, and recovery of background workers during deployments and maintenance activities.
Site Reliability Engineering & Production Operations
Build and maintain dashboards, alerts, logs, and traces across applications, Kubernetes clusters, databases, APIs, and background jobs.
Work with monitoring and observability tools such as Azure Monitor, Prometheus, Grafana, and OpenTelemetry.
Participate in on-call rotations and production incident troubleshooting.
Follow operational runbooks, escalation procedures, and incident management practices.
Automate smoke tests, health checks, operational diagnostics, and routine recovery activities.
Monitor deployment frequency, change failure rate, Mean Time to Recovery (MTTR), and service availability.
Identify recurring operational issues and implement automation to reduce operational toil.
Security Operations & Cloud Cost Optimization
Integrate vulnerability, dependency, and container image scanning into CI/CD pipelines.
Support vulnerability remediation and security validation across infrastructure and application deployments.
Implement least-privilege access, secure secrets management, and Kubernetes security baselines.
Maintain audit-friendly infrastructure changes and secure deployment practices in regulated environments.
Implement cloud cost tagging and dashboards across environments, services, and customers.
Monitor cloud consumption and investigate unexpected infrastructure spending.
Identify optimization opportunities through Kubernetes workload rightsizing, autoscaling, and removal of unused resources.
Balance cloud cost efficiency with platform reliability, performance, and security.
Required Experience
DevOps & Cloud Infrastructure (Must-Have)
Approximately 4 years of hands-on experience in DevOps, cloud infrastructure, platform engineering, or Site Reliability Engineering.
Practical experience with Kubernetes, Docker, Helm, Git, and Linux.
Working experience with Microsoft Azure cloud services, preferably Azure Kubernetes Service (AKS).
Understanding of container registries, cloud networking, storage, identity, and monitoring.
Experience with at least one CI/CD platform such as Azure DevOps, GitHub Actions, or Jenkins.
Understanding of cloud-native architectures and microservices deployment practices.
CI/CD, Automation & Infrastructure as Code
Experience building and maintaining automated CI/CD pipelines.
Working knowledge of GitOps principles and infrastructure automation.
Familiarity with Terraform, OpenTofu, or equivalent Infrastructure as Code tools.
Hands-on scripting experience using Python or Bash.
Understanding of deployment strategies, release versioning, configuration management, and rollback procedures.
Kubernetes & Production Troubleshooting
Experience deploying and troubleshooting applications in Kubernetes environments.
Understanding of pods, deployments, services, ingress, storage, networking, and autoscaling.
Ability to troubleshoot distributed services using logs, metrics, kubectl, Linux commands, and networking fundamentals.
Understanding of production monitoring, application health checks, and incident troubleshooting.
Familiarity with secure deployment practices and production change controls.
Database & Distributed Systems Fundamentals
Basic working knowledge of PostgreSQL and database operations.
Understanding of database backup, recovery, schema migrations, and data validation.
Exposure to asynchronous processing, distributed workflows, and event-driven architectures.
Understanding of operational reliability, fault tolerance, and recovery mechanisms.
Security & Operational Ownership
Understanding of vulnerability scanning, dependency management, and container security.
Familiarity with secrets management, access controls, and infrastructure security.
Strong ownership and accountability when supporting production systems.
Good documentation, communication, and troubleshooting skills.
Preferred Technical Stack Experience
Cloud: Microsoft Azure, Azure Kubernetes Service (AKS), AWS.
Containerization: Kubernetes, Docker, Helm.
CI/CD: Azure DevOps, GitHub Actions, Jenkins.
GitOps: Argo CD, Flux.
Infrastructure as Code: Terraform, OpenTofu.
Scripting: Python, Bash, Go.
Databases: PostgreSQL.
Workflow Orchestration: Temporal.
Messaging & Distributed Systems: Kafka.
Observability: Azure Monitor, OpenTelemetry, Prometheus, Grafana, Kubesense.
Security: Azure Key Vault, vulnerability scanning, container security.
Cloud Cost Management: Azure Cost Management, FinOps tagging and cost attribution.
Builder Mindset (Non-Negotiable)
Hands-on engineering mindset with a passion for automation and problem-solving.
Strong ownership and willingness to take responsibility for production systems.
Comfortable diagnosing technical issues and working through ambiguity.
Proactive approach to identifying repetitive tasks and eliminating manual operational effort.
Strong curiosity and willingness to learn new technologies and engineering practices.
Ability to collaborate effectively with application, platform, QA, and SRE teams.
AI-first, AI-fast approach to engineering productivity and operational problem-solving.
Outcome-driven mindset - focused on reliability, efficiency, and measurable impact.
What Success Looks Like
Reliable and repeatable deployments across development, QA, staging, and production environments.
Reduced manual intervention through CI/CD and infrastructure automation.
Stable Kubernetes deployments and improved cloud infrastructure reliability.
Well-maintained Helm charts, GitOps configurations, and deployment pipelines.
Automated deployment validations, smoke tests, and rollback procedures.
Improved observability across applications, databases, infrastructure, and distributed workflows.
Reliable database backup, recovery, and deployment validation processes.
Stronger security practices across infrastructure and deployment pipelines.
Improved cloud cost visibility and resource utilization.
Reduced operational toil and faster incident troubleshooting.
First 90 Days
Independently support standard AKS deployments.
Troubleshoot common Kubernetes and infrastructure issues.
Understand existing CI/CD pipelines and maintain operational runbooks.
Deliver meaningful automation improvements.
Within 6 Months
Own selected CI/CD pipelines, Helm charts, and GitOps configurations.
Implement automated release validations.
Improve visibility into service health and cloud spending.
Within 12 Months
Contribute to reliable multi-customer deployment workflows.
Support tested recovery and rollback procedures.
Reduce manual operational effort through automation.
Demonstrate measurable improvements in operational reliability and cloud cost efficiency.
This Role Is Not For You If
You prefer manual infrastructure management over automation.
You are not comfortable troubleshooting Kubernetes and production infrastructure issues.
You have experience only in monitoring without hands-on deployment and automation exposure.
You are not interested in learning cloud-native technologies and distributed systems.
You prefer working independently without collaborating with engineering teams.
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:
Scalable and reliable cloud-native platforms.
Automated and standardized multi-customer deployments.
Secure and resilient healthcare technology infrastructure.
Reliable data processing and workflow orchestration.
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.