Senior Platform Engineer — Infrastructure & DevOps

Job description

Senior Platform Engineer — Infrastructure & DevOps Embed with our platform team to own the hosting, CI/CD, security and operations layer the rest of engineering builds on. Position Overview: Anaqua is hiring a Senior Infrastructure & DevOps Engineer in Hyderabad to embed with our platform team. Together with the team you will own the hosting, CI/CD, security and operations layer the rest of engineering depends on — from GCP infrastructure and multi-region GKE to GitLab pipelines, edge security, secret management, observability and incident response for the new Anaqua / RightHub stack. Hands-on infra. Hands-on automation. Java is not part of this role — your delivery is the platform underneath. You'll love this job if you like to: Own the GCP infrastructure with the team — GKE clusters, multi-region setup, global load balancing, autoscaling, VPC networking, DNS, firewall rules and IAM. Build and maintain GitLab CI/CD pipelines and shared CI templates that every service team consumes — build, scan, deploy, promote across Dev / QA / Staging / Pre-Prod / Production. Help shape the company-wide standards for how services get deployed, secured, monitored and rolled back. Operate and harden the cluster — node pool upgrades, namespace / RBAC / resource-quota design, rolling updates, health probes, base images and supply-chain security. Run the platform security stack — gateway policies, API-key and JWT issuance, secret rotation, OWASP and dependency scanning, workload identity, IAM least-privilege. Own observability and incident response on GCP — structured logging, metrics, dashboards, SLIs / SLOs / error budgets, alerting, post-mortems and on-call runbooks. Build internal developer tooling — CLIs, self-service workflows and golden-path automation that make the next service easy to ship. What you will need to be successful: Strong production ownership on GCP — operating real workloads, not just standing up demos. GCP is the cloud we run on. Kubernetes in production (GKE) — deployments, Helm, namespaces, RBAC, resource quotas, rolling updates, health and readiness probes, multi-region setups and rollbacks. Terraform as a daily tool — modular, reusable modules with remote state, drift detection and clean management of IAM, networking, Pub/Sub, Cloud SQL and secrets. CI/CD pipeline depth — GitLab CI (or equivalent) at scale; reusable templates, fast feedback loops, security and dependency scans as pipeline stages, deploy promotion across Dev / QA / Staging / Pre-Prod / Production. Git workflow fluency — GitFlow or trunk-based branching, tagging and release strategies that fit a multi-service org. Cloud networking depth — VPC design, load balancing (global and regional), DNS, firewall rules and network security groups. Hosting and application security ownership — gateway and edge policies, secret rotation, OWASP and dependency scanning, workload identity, IAM least-privilege hygiene. Production observability and reliability on GCP — structured logs, metrics, dashboards, alerting, SLIs / SLOs / error budgets, on-call rotations, post-mortems. Performance work — load testing, capacity planning and operational tuning of services under real traffic. Operational PostgreSQL — migrations under load, backups, restores, replication basics, query plans and indexing. Asynchronous messaging on GCP Pub/Sub — topology, subscriptions, dead-letter handling and operational tuning. Pub/Sub is our primary message bus. Scripting and automation — Bash plus one of Python or Go for internal tooling and platform automation. Excellent written and spoken English; comfortable working across time zones with engineers in EU and the US. AI-first mindset Treats AI tooling as a daily collaborator, not a gimmick — Claude Code, Cursor, Copilot in the daily workflow. Builds platform tooling, IaC modules, runbooks, dashboards and structured logs that both humans and AI agents can work against. Has a view on AI in the SDLC — agent-assisted code review, AI-generated runbooks and post-mortems, codegen scaffolding for CI templates and Terraform modules. Sensible about secrets, audit trails and data boundaries when AI integrations touch internal systems. Professional skills and mindset End-to-end on your work — designs, ships, monitors and debugs. Writes — design docs, RFCs, runbooks. Decisions get documented, not just made. Pragmatic — ships value before perfect abstractions. Raises the bar with peers, not by gate-keeping; happy to share knowledge across the team. Comfortable making calls under ambiguity and changing them when the data says so. Strong customer and business empathy — connects platform work back to product impact. Collaborates well across time zones with engineers in EU and the US — opinions held lightly, decisions made together. A plus, not required GCP Professional Cloud Architect or Professional Cloud DevOps Engineer certification. gRPC, Envoy or GKE Gateway API operating experience. Broader messaging and streaming exposure — Kafka, RabbitMQ or similar — for breadth alongside our GCP Pub/Sub usage. Cost / FinOps practice on GCP — budgets, alerts, rightsizing. Supply-chain security — SBOM, image signing, SLSA, container scanning at scale. Background in IP management, legal-tech or regulated B2B SaaS.