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Application Reliability Engineer

5 hours, 56 minutes ago
United States
Full-time
Mid Level
Site Reliability Engineer (SRE)
Software Development
API Gateway Apigee CI/CD Docker Firestore GCP Generative AI GitHub Actions GitLab CI Go gRPC Java JavaScript Jenkins Kubernetes LLM Load Balancing Looker Microservices Node.js Python REST API SQL Tableau Terraform Vertex AI
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Innodata

Innodata

Innodata Inc. is a global leader in data engineering, offering end-to-end AI solutions and platforms for businesses worldwide, combining AI and human expertise to solve complex data challenges.

IT Services
1K-5K
Founded 1988
View All Jobs 24

Description

  • Provide production support and maintenance for enterprise applications hosted on Google App Engine.
  • Triage, diagnose, restore service, and resolve user-impacting incidents within agreed SLAs and SLOs.
  • Troubleshoot application errors, performance issues, configuration problems, and service or integration failures.
  • Design, develop, and deliver feature enhancements and functional improvements to existing applications.
  • Support microservices architecture, including APIs, service boundaries, authentication, and inter-service behavior.
  • Own build, release, and deployment activities across development, test, pre-production, and production environments.
  • Manage App Engine deployments, including versioning, traffic splitting, canary rollouts, scaling, and rollbacks.
  • Perform root-cause analysis for recurring production issues and implement sustainable fixes.
  • Build and maintain monitoring, alerting, logging, dashboards, and error reporting.
  • Support platform, framework, dependency, and runtime upgrades while preserving stability and compliance.
  • Support IAM, service accounts, access controls, secrets management, and operational governance.
  • Participate in change management, release-readiness reviews, and on-call or rotational support.
  • Collaborate with client, engineering, product, QA, data engineering, infrastructure, and platform teams.
  • Create and maintain technical documentation, runbooks, troubleshooting guides, deployment procedures, and support playbooks.

Requirements

  • 3-7 years of experience in Application Support, Application Engineering, Software Engineering, Cloud Engineering, or a related role.
  • Hands-on experience supporting production applications on Google Cloud Platform (GCP).
  • Hands-on experience with Google App Engine, including deployment, configuration, scaling, versioning, and troubleshooting.
  • Solid understanding of microservices architecture, REST/gRPC APIs, service-to-service communication, distributed tracing, and cross-service debugging.
  • Practical experience with deployments across multiple environments, including release validation, rollback, and change control.
  • Strong programming skills in one or more of Python, Java, Node.js/JavaScript, or Go.
  • Working knowledge of SQL and data stores such as Cloud SQL, Firestore/Datastore, Cloud Spanner, or BigQuery.
  • Good understanding of GCP IAM, service accounts, permissions, monitoring, logging, alerting, and production operations.
  • Experience with CI/CD pipelines and build/deployment tools such as Cloud Build, Jenkins, GitHub Actions, or GitLab CI.
  • Experience troubleshooting complex production environments and performing root-cause analysis under time pressure.
  • Ability to quickly understand existing systems, codebases, services, configurations, and client-specific workflows.
  • Strong communication and collaboration skills, including during user-impacting incidents.
  • Preferred: experience supporting large-scale enterprise applications with high availability and performance requirements.
  • Preferred: Cloud Run, GKE, Cloud Functions, or other GCP application services.
  • Preferred: Apigee/API Gateway, load balancing, and API management.
  • Preferred: Pub/Sub, Cloud Tasks, Cloud Scheduler, and asynchronous or event-driven patterns.
  • Preferred: Infrastructure as Code, especially Terraform.
  • Preferred: SRE practices including SLIs/SLOs, error budgets, incident management, and blameless postmortems.
  • Preferred: containerization with Docker and Kubernetes fundamentals.
  • Preferred: frontend or full-stack experience supporting user-facing web applications.
  • Preferred: Looker, Tableau, or BI/reporting integrations.
  • Preferred: supporting AI/ML, GenAI, or LLM-based applications on GCP, including Vertex AI.

Benefits

  • Expected salary range of $60,000-$100,000 USD per year, based on experience, skills, and qualifications.

Interested in this position?

Apply directly on the company website

Apply Now

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