{"id":3856151,"url":"https://alion.io/job/rhythmx-ai-engineering-manager-platform-reliability","title":"Engineering Manager – Platform Reliability","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":"Leadership","role_family":"Leadership","seniority":"lead","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":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure AKS","optional":false},{"name":"Bash","optional":false},{"name":"Canary Release","optional":false},{"name":"CI/CD","optional":false},{"name":"Configuration Management","optional":false},{"name":"Docker","optional":false},{"name":"FHIR","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":"HIPAA","optional":false},{"name":"HL7","optional":false},{"name":"Incident Management","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Least Privilege","optional":false},{"name":"Linux","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Platform Engineering","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SOC 2","optional":false},{"name":"ArgoCD","optional":true},{"name":"OpenTofu","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-11-06T05:01:44Z","employer_posted_date":"2026-11-06","last_verified_at":"2026-11-07T13:10:58Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Engineering Manager - Platform Reliability\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\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 an Engineering Manager - Platform Reliability, you will lead and drive our DevOps, Site Reliability Engineering (SRE), and DevSecOps capabilities, ensuring the platform is highly available, secure, scalable, and reliable across multiple customer environments.\nYou will own the architecture and execution of deployment automation, Kubernetes infrastructure, database reliability, production operations, security, and cloud cost optimization.\nThis is a highly technical, hands-on leadership role requiring deep expertise in cloud infrastructure, distributed systems, CI/CD, Kubernetes, and production reliability. You will work closely with application, data, AI/ML, QA, and product engineering teams to build standardized, automated, and resilient platform operations.\nWhat You'll Own\nDeployment Architecture & Release Engineering\n\nArchitect and implement standardized, automated CI/CD pipelines across development, QA, staging, and production environments.\n\nDrive reliable, repeatable, and near one-click deployments across multiple customer environments.\n\nDesign and implement Blue/Green and Canary deployment strategies to minimize downtime and release risks.\n\nEnable independent deployment of application code, configurations, and database changes with safe rollback and recovery mechanisms.\n\nImplement automated pre- and post-deployment validations, release versioning, artifact promotion, and deployment traceability.\n\nReduce deployment duration, manual intervention, and change failure rates.\n\nKubernetes & Cloud Infrastructure Management\n\nOwn Kubernetes-based platform architecture and operations across Microsoft Azure and AWS.\n\nDrive infrastructure provisioning and deployment automation using Infrastructure as Code (IaC).\n\nEstablish GitOps-based management of Kubernetes manifests, Helm charts, and application configurations.\n\nDesign reusable infrastructure templates to support multiple customer environments.\n\nAutomate environment provisioning, including production-like environments using synthetic or de-identified healthcare data.\n\nOptimize Kubernetes scheduling, autoscaling, capacity, availability, and cloud resource utilization.\n\nEnsure proper separation of application artifacts, environment configurations, secrets, and persistent data.\n\nDatabase Operations & Data Reliability\n\nOwn production database reliability, particularly PostgreSQL, including backup, recovery, high availability, and disaster recovery.\n\nDesign automated schema migrations, database upgrades, and safe rollback and recovery procedures.\n\nImplement database replication, synchronization, and Change Data Capture (CDC) mechanisms where required.\n\nEstablish Git-controlled reference data, seed data, and configuration management.\n\nAutomate database connectivity, integrity, and post-migration validation checks.\n\nDefine and regularly test Recovery Time Objectives (RTO) and Recovery Point Objectives (RPO).\n\nPartner with development teams to enable backward-compatible schema evolution and database backfills.\n\nSite Reliability Engineering & Production Operations\n\nEstablish Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error-budget practices.\n\nBuild end-to-end observability across microservices, infrastructure, databases, APIs, and distributed workflows.\n\nImplement centralized logging, metrics, distributed tracing, dashboards, and actionable alerting.\n\nLead production incident management, root cause analysis (RCA), and corrective action tracking.\n\nDevelop automated operational runbooks, diagnostics, and recovery procedures.\n\nDrive production-readiness reviews, performance testing, capacity planning, and operational risk assessments.\n\nContinuously improve platform availability, Mean Time to Recovery (MTTR), and operational efficiency.\n\nDistributed Systems & Workflow Reliability\n\nOwn operational reliability of distributed systems involving Kubernetes, Kafka, Temporal, and asynchronous workers.\n\nDesign safe pause, drain, resume, and ownership-transfer mechanisms during application deployments.\n\nPrevent duplicate or missed processing and unintended external side effects during system upgrades.\n\nMonitor and recover scheduled jobs, background workers, and long-running workflows.\n\nPartner with engineering teams to implement retries, idempotency, backpressure, rate limiting, and fault-tolerant recovery mechanisms.\n\nSecurity Operations & Compliance (DevSecOps)\n\nOwn DevSecOps practices across infrastructure, CI/CD pipelines, Kubernetes, and production environments.\n\nIntegrate vulnerability scanning, container image scanning, dependency scanning, and automated security validations.\n\nEstablish secure secrets and certificate management, least-privilege access, and production access controls.\n\nStrengthen audit logging, network security, and infrastructure hardening.\n\nEmbed security controls into infrastructure provisioning and release automation.\n\nSupport HIPAA, HITRUST, and SOC 2 compliance through technical safeguards, operational controls, and audit evidence collection.\n\nCoordinate vulnerability remediation and security incident response with security and compliance teams.\n\nEnsure sensitive healthcare data is protected across development, testing, staging, and production environments.\n\nCloud Cost Management & Optimization (FinOps)\n\nOwn cloud cost visibility, tracking, forecasting, and optimization across Azure/AWS infrastructure, Kubernetes workloads, databases, storage, networking, and observability.\n\nEstablish accurate cloud cost allocation and reporting by customer, environment, service, and engineering team.\n\nImplement budgets, spend dashboards, cost anomaly detection, and proactive alerts for unexpected consumption.\n\nOptimize resource utilization through rightsizing, autoscaling, capacity planning, storage lifecycle policies, and reserved or spot capacity.\n\nPartner with engineering and finance teams to evaluate unit economics and cost-performance trade-offs.\n\nDefine and track FinOps KPIs, including budget variance, resource utilization, cost per customer/workload, and verified infrastructure savings without compromising reliability or security.\n\nEngineering Leadership & Operational Excellence\n\nBuild, mentor, and lead high-performing DevOps, SRE, and security engineering teams.\n\nProvide hands-on technical leadership across architecture, automation, troubleshooting, and production incident management.\n\nDefine on-call coverage, escalation pathways, and operational ownership.\n\nCollaborate closely with application, data, AI/ML, QA, and product engineering teams.\n\nEstablish a culture of automation, standardization, accountability, and continuous improvement.\n\nEvaluate AI-assisted incident investigation, log analysis, automated root cause analysis, and operational diagnostics.\n\nPrioritize reliability improvements and technical debt alongside product delivery.\n\nMeasure engineering effectiveness through DORA metrics and platform reliability indicators.\n\nRequired Experience\nEngineering Leadership & Platform Reliability (Must-Have)\n12+ years of experience in software engineering, infrastructure, DevOps, or Site Reliability Engineering, with proven technical leadership.\n\nAt least 4+ years of experience in technical leadership or engineering management.\n\nProven experience designing, building, and operating cloud-native production platforms.\n\nStrong hands-on expertise in Kubernetes, Docker, Helm, and microservices-based architectures.\n\nAbility to investigate complex production issues directly while mentoring and developing engineering teams.\n\nDemonstrated experience leading production incidents, root cause analysis, and corrective actions.\n\nCloud Infrastructure & DevOps Expertise (Must-Have)\nDeep practical experience with Microsoft Azure, particularly AKS, networking, storage, identity, and managed databases.\n\nExperience working with AWS cloud infrastructure.\n\nStrong CI/CD experience using GitHub Actions, Jenkins, or equivalent tools.\n\nHands-on experience with GitOps, Infrastructure as Code (IaC), and environment automation.\n\nExperience designing automated deployment pipelines and release management strategies.\n\nStrong Linux administration, networking, and infrastructure troubleshooting skills.\n\nDatabase & Distributed Systems Expertise\nStrong production experience with PostgreSQL, including backup, recovery, database migrations, replication, and high availability.\n\nUnderstanding of database schema evolution, CDC, and zero-downtime migration strategies.\n\nExperience operating distributed systems, asynchronous processing, and event-driven architectures.\n\nProficiency in Python, Go, Bash, or comparable automation languages.\n\nStrong understanding of fault tolerance, retries, idempotency, and failure recovery.\n\nSRE, Observability & Security\nExperience implementing SLIs, SLOs, error budgets, and reliability engineering practices.\n\nHands-on experience with monitoring, logging, distributed tracing, and incident management.\n\nExperience implementing cloud security and CI/CD security controls.\n\nStrong understanding of secrets management, access controls, vulnerability scanning, and infrastructure hardening.\n\nFamiliarity with HIPAA, HITRUST, SOC 2, or other regulated industry compliance requirements.\n\nCloud Cost Management & FinOps\nExperience managing and optimizing cloud infrastructure costs across Azure/AWS.\n\nUnderstanding of cloud budgets, cost allocation, resource utilization, and infrastructure forecasting.\n\nExperience implementing cost monitoring, anomaly detection, and optimization initiatives.\n\nAbility to balance infrastructure cost efficiency with platform reliability, scalability, and security.\n\nPreferred Technical Stack Experience\nCloud: Microsoft Azure (AKS preferred), AWS.\n\nContainerization & Orchestration: Kubernetes, Docker, Helm.\n\nCI/CD & GitOps: GitHub Actions, Jenkins, Argo CD, Flux.\n\nInfrastructure as Code: Terraform, OpenTofu, or equivalent.\n\nDatabases: PostgreSQL, database replication, CDC.\n\nDistributed Systems: Kafka, Temporal, event-driven architectures.\n\nObservability: OpenTelemetry, Prometheus, Grafana, Azure Monitor, AWS Monitor.\n\nSecurity: DevSecOps, vulnerability scanning, secrets management, infrastructure security.\n\nHealthcare Interoperability: HL7, FHIR, clinical data processing workflows.\n\nFinOps: Azure/AWS Cost Management, Kubernetes cost attribution, cloud cost optimization.\n\nBuilder Mindset (Non-Negotiable)\nHands-on engineering mindset with strong architectural and troubleshooting capabilities.\n\nStrong ownership and bias for execution.\n\nComfortable operating in ambiguity and solving complex infrastructure and production challenges.\n\nAbility to balance technical depth, people leadership, and business priorities.\n\nPassion for automation, reliability, scalability, and operational excellence.\n\nAI-first, AI-fast approach to engineering and operational problem-solving.\n\nOutcome-driven mindset - focused on measurable improvements rather than operational activity.\n\nWhat Success Looks Like\nStandardized and automated deployment workflows across customer environments.\n\nReliable, repeatable releases with minimal manual 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