Application Reliability Engineer

Innodata(Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked.

Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted  provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.

We are looking for a hands-on Application Support Engineer to support, maintain, and enhance business-critical enterprise applications built and running on Google App Engine (GAE) and microservices. The role is focused on application availability, production support, incident response, troubleshooting, and continuous feature enhancement rather than building a new application from the ground up. The ideal candidate can quickly understand an existing microservices-based application landscape, restore service when users are impacted, and deliver incremental enhancements safely across test, pre-production, and production environments.

Experience supporting large-scale, business-critical applications in complex enterprise technology environments is preferred.

Provide production support and maintenance for enterprise applications hosted on Google App Engine, including standard and flexible environments. Act as a first point of contact for user-impacting incidents: triage, diagnose, restore service, and drive issues to closure within agreed SLAs/SLOs. Troubleshoot application errors, failed requests, latency and performance degradation, service-to-service failures, configuration issues, quota/scaling limits, and dependency or integration failures. Design, develop, and deliver feature enhancements and functional improvements to existing applications based on user and business needs.

Support applications built on microservices architecture, including service boundaries, APIs/contracts, inter-service communication, authentication, and failure/retry behavior. Own build, release, and deployment activities across development, test, pre-production, and production environments with appropriate validation, approvals, and rollback plans. Manage App Engine deployments including versions, traffic splitting/migration, canary and staged rollouts, rollbacks, service configuration, and scaling settings. Perform root-cause analysis for recurring production issues and implement sustainable fixes.

Build and maintain monitoring, alerting, logging, dashboards, and error reporting using Cloud Monitoring, Cloud Logging, Error Reporting, and Cloud Trace. Support platform, framework, library, dependency, and runtime upgrades while maintaining stability, supportability, and compliance. Support IAM, service accounts, access controls, secrets management, and operational governance. Participate in change management, release-readiness reviews, and on-call/rotational support as required. Collaborate with client-specific Application Engineering, Product, QA, Data Engineering, Infrastructure, and Platform teams.

Adapt to established client-specific engineering, security, review, change-management, and operational processes. Create and maintain technical documentation, operational runbooks, troubleshooting guides, deployment procedures, and support playbooks.

Service decomposition and ownership: understand service boundaries, upstream/downstream dependencies, and ownership of behavior or data. APIs and contracts: REST and gRPC/protobuf interfaces, versioning, backward compatibility, and contract-change impacts. Inter-service communication: synchronous calls, asynchronous/event-driven messaging (Pub/Sub, Cloud Tasks), idempotency, retries, timeouts, backoff, and circuit breaking. Service-to-service authentication and authorization using service accounts, identity/tokens, and least-privilege access. Distributed troubleshooting using logs, distributed tracing, and correlation IDs to isolate failures across services.

Failure modes at scale, including cascading failures, partial outages, hot spots, quota exhaustion, and graceful degradation. Independent deployability and coordination of multi-service releases when required. Service-level observability, including dashboards, SLIs/SLOs, alerting, and error budgets.

3-7 years of experience in Application Support, Application Engineering, Software Engineering, Cloud Engineering, or a related role. Strong hands-on experience supporting, maintaining, and enhancing 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 and…