Lead DevOps & Cloud Infrastructure Engineer
This is a hands-on lead role owning the cloud infrastructure and DevOps function for Astreya's product portfolio. Google Cloud is the primary platform; This is not a role that sets direction and hands the work to someone else: the expectation is that this person writes the Terraform, debugs the cluster, runs the deployment, and then mentors the engineers who will do it next time. They act as the subject matter expert for infrastructure across product, engineering and delivery teams, and as the technical owner in customer conversations about deployment, security and hosting models.
Owns the infrastructure and deployment layer end to end, from CI pipeline to production runtime, across multiple products on independent release cadences
Resolves complex problems where the diagnosis requires in-depth evaluation of many interacting variables — networking, identity, cluster behaviour, managed service limits, cost
Cloud infrastructure (primary)
GKE, Artifact Registry, Cloud SQL (Postgres), Cloud Storage, Memorystore (Redis), Vertex AI, Cloud Monitoring/Logging, Cloud DNS
Own network and perimeter design: VPC architecture, Private Service Connect, Cloud NAT, Cloud Armor, private connectivity to customer systems
Secret Manager, Workload Identity, IAM design and least-privilege service accounts, KMS, certificate lifecycle
Run R&D; on platform services we haven't used yet — evaluate the GCP service, identify the Azure and AWS equivalents, and produce a recommendation with a working proof of concept, not a slide
Manage cloud cost: attribution by product and environment, budget alerts, rightsizing, commitment planning
Deployment into environments (a core reason this role exists)




Own the deployment artefacts: Helm charts, namespace and pod topology, environment configuration, migration and rollback paths
Produce and maintain the evidence infrastructure security reviews and audits ask for: architecture diagrams, data flow, access controls, encryption posture, audit logging, retention
DevOps and platform engineering
Own CI/CD across products: build pipelines, artefact promotion, workplace strategy, source control branching strategies across multiple release cadences
Write automation and internal tooling for provisioning and operating infrastructure — infrastructure as code (Terraform) as the default, scripts and services where it isn't
Improve scalability, reliability, capacity and performance of the platform, including the infrastructure serving AI/LLM workloads
Harden the platform: image scanning, dependency and vulnerability management, network policy, secrets hygiene, patching
Lead and mentor DevOps and infrastructure engineers; Own incident response for platform issues and produce root cause analyses for outages that are honest about cause and specific about prevention
This list is not a comprehensive inventory of all responsibilities assigned to this position
Bachelor's degree (B.S/B.A)



from a four-year college or university and 8+ years' related experience and/or training; or an equivalent combination of education and experience
Deep, hands-on Google Cloud experience — has designed and run production workloads on GCP, not just passed a certification
Strong Kubernetes experience in production: GKE preferred, including networking, ingress, autoscaling, resource management and debugging failures under load
Strong scripting and coding ability (Python, Go, Bash or equivalent) and enough software development experience to work inside application repositories, not just around them
Practical cloud networking and security depth: VPC design, private connectivity, IAM, secrets management, TLS
Monitoring, alerting and incident management experience, including writing the RCA afterwards
Experience with open-source tooling in large distributed systems
Working Azure knowledge (AKS, Key Vault, Entra ID, VNet) and the ability to translate a GCP design onto it; AWS exposure a bonus
Experience deploying a product into customer-controlled cloud environments as a vendor
Experience supporting AI/ML workloads in production — Vertex AI, model endpoints, GPU scheduling, inference cost control
Experience integrating with enterprise ITSM platforms (ServiceNow) and the connectivity that requires
Prior experience as a first or early infrastructure hire on a product team
Relevant certification (Google Professional Cloud Architect, Professional Cloud DevOps Engineer, CKA)
Must have the ability to perform office-related tasks which may include prolonged sitting or standing
Must have the ability to move from place to place within an office environment
Must be able to use a computer

📌 Cloud Infrastructure DevOps Engineer (India)
🏢 Astreya
📍 India