Senior Platform Engineer — Infrastructure & DevOps

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.
• Kubernetesin production (GKE) — deployments, Helm, namespaces, RBAC, resource quotas, rolling updates, health and readiness probes, multi-region setups and rollbacks.
• Terraformas 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 andapplication securityownership — gateway and edge policies, secret rotation, OWASP and dependency scanning, workload identity, IAM least-privilege hygiene.
• Production observability and reliability onGCP— 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 GCPPub/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.