{"id":3856150,"url":"https://alion.io/job/rhythmx-ai-devops-engineer","title":"DevOps Engineer","company":{"id":691488,"name":"RhythmX AI","domain":"rhythmxai.com","url":"https://alion.io/company/rhythmxai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"ArgoCD","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Azure DevOps","optional":false},{"name":"Bash","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Docker","optional":false},{"name":"FinOps","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitOps","optional":false},{"name":"Grafana","optional":false},{"name":"Helm","optional":false},{"name":"Incident Management","optional":false},{"name":"Jenkins","optional":false},{"name":"kubectl","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"Linux","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"OpenTofu","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Terraform","optional":false},{"name":"AWS","optional":true}],"status":"live","first_seen_at":"2026-11-06T05:17:46Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-07T08:56:22Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"DevOps Engineer\nAbout GW RhythmX\nOur Vision: Forever change medicine by turning intelligence into impact at every point of care.\nGW 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.\nAs a Symphony AI portfolio company, we combine startup agility with enterprise-scale infrastructure, including:\nLongitudinal data on 300M patients\n4.4B annual claims\nA global network of 1.8M healthcare professionals\n\nThe Role\nWe 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.\nAs a DevOps Engineer, you will help build and operate secure, reliable, and repeatable cloud-native deployments for our healthcare SaaS platform.\nYou 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.\nThis 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.\nWhat You'll Own\nCI/CD, Release Engineering & GitOps\n\nBuild and maintain CI/CD pipelines for microservices, automating build, test, container image publishing, artifact promotion, and deployment.\n\nMaintain Helm charts, Kubernetes manifests, and GitOps workflows using Argo CD or Flux.\n\nSupport standardized and repeatable deployment workflows across development, QA, staging, and production environments.\n\nImplement deployment preflight checks, smoke tests, automated validations, and rollback procedures.\n\nSupport Blue/Green deployment strategies, traffic cutovers, and controlled service draining.\n\nMaintain version-controlled release scripts, deployment artifacts, environment variables, and configuration management.\n\nIdentify opportunities to reduce manual deployment activities and improve release efficiency.\n\nCloud Infrastructure, Kubernetes & Automation\n\nDeploy, monitor, and troubleshoot applications running on Azure Kubernetes Service (AKS).\n\nWork with Kubernetes components including pods, nodes, networking, ingress, storage, and autoscaling.\n\nUse Terraform/OpenTofu and Infrastructure as Code (IaC) practices to provision and configure reproducible environments.\n\nAutomate provisioning of development, QA, and production-like environments using approved synthetic or de-identified test data.\n\nDevelop Python, Bash, or Go utilities to automate operational tasks, diagnostics, and infrastructure validation.\n\nSupport cloud infrastructure reliability, scalability, availability, and resource optimization.\n\nDatabase Operations & Workflow Reliability\n\nSupport PostgreSQL operations, including backup verification, restore drills, connectivity changes, monitoring, and basic performance troubleshooting.\n\nAssist with automated database schema migration workflows and post-deployment data validation.\n\nCollaborate with engineering teams to support safe database rollout and rollback procedures.\n\nImplement Git-backed processes to manage and validate reference data, seed data, and feature flags across environments.\n\nMonitor asynchronous processing, scheduled jobs, and distributed workloads involving Temporal and Kafka.\n\nSupport safe pause, resume, and recovery of background workers during deployments and maintenance activities.\n\nSite Reliability Engineering & Production Operations\n\nBuild and maintain dashboards, alerts, logs, and traces across applications, Kubernetes clusters, databases, APIs, and background jobs.\n\nWork with monitoring and observability tools such as Azure Monitor, Prometheus, Grafana, and OpenTelemetry.\n\nParticipate in on-call rotations and production incident troubleshooting.\n\nFollow operational runbooks, escalation procedures, and incident management practices.\n\nAutomate smoke tests, health checks, operational diagnostics, and routine recovery activities.\n\nMonitor deployment frequency, change failure rate, Mean Time to Recovery (MTTR), and service availability.\n\nIdentify recurring operational issues and implement automation to reduce operational toil.\n\nSecurity Operations & Cloud Cost Optimization\n\nIntegrate vulnerability, dependency, and container image scanning into CI/CD pipelines.\n\nSupport vulnerability remediation and security validation across infrastructure and application deployments.\n\nImplement least-privilege access, secure secrets management, and Kubernetes security baselines.\n\nMaintain audit-friendly infrastructure changes and secure deployment practices in regulated environments.\n\nImplement cloud cost tagging and dashboards across environments, services, and customers.\n\nMonitor cloud consumption and investigate unexpected infrastructure spending.\n\nIdentify optimization opportunities through Kubernetes workload rightsizing, autoscaling, and removal of unused resources.\n\nBalance cloud cost efficiency with platform reliability, performance, and security.\n\nRequired Experience\nDevOps & Cloud Infrastructure (Must-Have)\nApproximately 4 years of hands-on experience in DevOps, cloud infrastructure, platform engineering, or Site Reliability Engineering.\n\nPractical experience with Kubernetes, Docker, Helm, Git, and Linux.\n\nWorking experience with Microsoft Azure cloud services, preferably Azure Kubernetes Service (AKS).\n\nUnderstanding of container registries, cloud networking, storage, identity, and monitoring.\n\nExperience with at least one CI/CD platform such as Azure DevOps, GitHub Actions, or Jenkins.\n\nUnderstanding of cloud-native architectures and microservices deployment practices.\n\nCI/CD, Automation & Infrastructure as Code\nExperience building and maintaining automated CI/CD pipelines.\n\nWorking knowledge of GitOps principles and infrastructure automation.\n\nFamiliarity with Terraform, OpenTofu, or equivalent Infrastructure as Code tools.\n\nHands-on scripting experience using Python or Bash.\n\nUnderstanding of deployment strategies, release versioning, configuration management, and rollback procedures.\n\nKubernetes & Production Troubleshooting\nExperience deploying and troubleshooting applications in Kubernetes environments.\n\nUnderstanding of pods, deployments, services, ingress, storage, networking, and autoscaling.\n\nAbility to troubleshoot distributed services using logs, metrics, kubectl, Linux commands, and networking fundamentals.\n\nUnderstanding of production monitoring, application health checks, and incident troubleshooting.\n\nFamiliarity with secure deployment practices and production change controls.\n\nDatabase & Distributed Systems Fundamentals\nBasic working knowledge of PostgreSQL and database operations.\n\nUnderstanding of database backup, recovery, schema migrations, and data validation.\n\nExposure to asynchronous processing, distributed workflows, and event-driven architectures.\n\nUnderstanding of operational reliability, fault tolerance, and recovery mechanisms.\n\nSecurity & Operational Ownership\nUnderstanding of vulnerability scanning, dependency management, and container security.\n\nFamiliarity with secrets management, access controls, and infrastructure security.\n\nStrong ownership and accountability when supporting production systems.\n\nGood documentation, communication, and troubleshooting skills.\n\nPreferred Technical Stack Experience\nCloud: Microsoft Azure, Azure Kubernetes Service (AKS), AWS.\n\nContainerization: Kubernetes, Docker, Helm.\n\nCI/CD: Azure DevOps, GitHub Actions, Jenkins.\n\nGitOps: Argo CD, Flux.\n\nInfrastructure as Code: Terraform, OpenTofu.\n\nScripting: Python, Bash, Go.\n\nDatabases: PostgreSQL.\n\nWorkflow Orchestration: Temporal.\n\nMessaging & Distributed Systems: Kafka.\n\nObservability: Azure Monitor, OpenTelemetry, Prometheus, Grafana, Kubesense.\n\nSecurity: Azure Key Vault, vulnerability scanning, container security.\n\nCloud Cost Management: Azure Cost Management, FinOps tagging and cost attribution.\n\nBuilder Mindset (Non-Negotiable)\nHands-on engineering mindset with a passion for automation and problem-solving.\n\nStrong ownership and willingness to take responsibility for production systems.\n\nComfortable diagnosing technical issues and working through ambiguity.\n\nProactive approach to identifying repetitive tasks and eliminating manual operational effort.\n\nStrong curiosity and willingness to learn new technologies and engineering practices.\n\nAbility to collaborate effectively with application, platform, QA, and SRE teams.\n\nAI-first, AI-fast approach to engineering productivity and operational problem-solving.\n\nOutcome-driven mindset - focused on reliability, efficiency, and measurable impact.\n\nWhat Success Looks Like\nReliable and repeatable deployments across development, QA, staging, and production environments.\n\nReduced manual intervention through CI/CD and infrastructure automation.\n\nStable Kubernetes deployments and improved cloud infrastructure reliability.\n\nWell-maintained Helm charts, GitOps configurations, and deployment pipelines.\n\nAutomated deployment validations, smoke tests, and rollback procedures.\n\nImproved observability across applications, databases, infrastructure, and distributed workflows.\n\nReliable database backup, recovery, and deployment validation processes.\n\nStronger security practices across infrastructure and deployment pipelines.\n\nImproved cloud cost visibility and resource utilization.\n\nReduced operational toil and faster incident troubleshooting.\n\nFirst 90 Days\nIndependently support standard AKS deployments.\n\nTroubleshoot common Kubernetes and infrastructure issues.\n\nUnderstand existing CI/CD pipelines and maintain operational runbooks.\n\nDeliver meaningful automation improvements.\n\nWithin 6 Months\nOwn selected CI/CD pipelines, Helm charts, and GitOps configurations.\n\nImplement automated release validations.\n\nImprove visibility into service health and cloud spending.\n\nWithin 12 Months\nContribute to reliable multi-customer deployment workflows.\n\nSupport tested recovery and rollback procedures.\n\nReduce manual operational effort through automation.\n\nDemonstrate measurable improvements in operational reliability and cloud cost efficiency.\n\nThis Role Is Not For You If\nYou prefer manual infrastructure management over automation.\n\nYou are not comfortable troubleshooting Kubernetes and production infrastructure issues.\n\nYou have experience only in monitoring without hands-on deployment and automation exposure.\n\nYou are not interested in learning cloud-native technologies and distributed systems.\n\nYou prefer working independently without collaborating with engineering teams.\n\nYou are not comfortable taking ownership of production reliability and operational responsibilities.\n\nWhy Join Us\nYou will contribute to building the core infrastructure that powers AI-driven healthcare applications, enabling:\nScalable and reliable cloud-native platforms.\n\nAutomated and standardized multi-customer deployments.\n\nSecure and resilient healthcare technology infrastructure.\n\nReliable data processing and workflow orchestration.\n\nNext-generation AI-powered healthcare applications.\n\nThis 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.","description_format":"text","description_chars":11625,"description_truncated":false,"requirements":{"experience_years_min":4,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"phd","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Medical AI","Clinical Decision 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