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.