<p><strong>The job in short</strong></p> <div class="custom-field-control editable-field-control" data-type="long_text"> <div class="collapsed-field"> <p>Backbase powers the financial experiences of many of the world's leading banks. Our engagement banking platform helps banks unify customer data, orchestrate journeys, and deliver personalized experiences across digital channels. We are increasingly <strong>AI-driven</strong> — using AI to accelerate product delivery, journey orchestration, and engineering workflows, including how we build, operate, and automate platform and release infrastructure.</p> <p><strong>Meet the job</strong></p> <div class="custom-field-control editable-field-control" data-type="long_text"> <div class="collapsed-field"> <p>We are hiring a <strong>System Engineer</strong> in <strong>Hyderabad</strong> for the <strong>Digital Sales</strong> team, which delivers <strong>Retail Onboarding</strong> capabilities used by leading banks across web, mobile, and backend services.</p> <p>You will own the DevOps and platform foundation for this domain end to end: <strong>release and commercial-release support</strong>, <strong>CI/CD and pipeline reliability</strong>, <strong>ephemeral and shared test environments</strong>, <strong>runtime readiness</strong>, <strong>secrets and third-party connector wiring</strong>, and <strong>infrastructure automation</strong> — so engineering and quality can deliver safely and repeatedly.</p> <p>This is a hands-on System Engineering / DevOps role. You partner with backend, mobile, frontend, and quality engineers in a distributed team to keep environments healthy, releases predictable, and pipelines trustworthy — and to <strong>apply AI and AI agents</strong> to automate operational work where it accelerates the team.</p> <h4>What you will do</h4> <h3>Release & commercial readiness</h3> <ul> <li>Support major and patch releases: runtime readiness, bootstrap/flow deployment checks, and release-day operational support.</li> <li>Own or improve release-readiness validations (e.g. component/BOM checks, dry-run commercial-release reliability, publishing health).</li> <li>Troubleshoot publisher / workflow / packaging failures and drive durable fixes — not one-off workarounds.</li> </ul> <h3>Environments & runtimes</h3> <ul> <li>Design, create, and maintain <strong>ephemeral and shared environments</strong> for flows and journeys (mock, sandbox, and direct modes as needed).</li> <li>Keep reference / staging / performance runtimes healthy for development and test execution.</li> <li>Wire <strong>Grand Central / connector connectivity</strong>, deploy credentials as secrets, and enable feature flags or payload options required for journey testing.</li> </ul> <h3>CI/CD, GitOps & automation</h3> <ul> <li>Own and improve <strong>GitHub Actions</strong> (and related) workflows across Digital Sales repositories: tagging schemes, quality gates, smoke/regression hooks, and pipeline stability.</li> <li>Work with containers and Kubernetes; manage configuration with <strong>Helm / Terraform</strong> and GitOps practices (<strong>Argo CD</strong> or equivalent).</li> <li>Automate repetitive DevOps tasks with <strong>Python / Go</strong> scripting and, increasingly, <strong>AI-assisted automation</strong>.</li> </ul> <h3>Platform & developer enablement</h3> <ul> <li>Partner with mobile and backend engineers on CI implications of repo/structure changes (e.g. modular monorepos, multi-module publish, migration effort).</li> <li>Improve observability and feedback loops (metrics, dashboards, logs/traces) so failures are visible early.</li> <li>Document runbooks and environment patterns in Confluence; collaborate in Jira with a distributed team.</li> <li>Participate in on-call / incident response for production and critical shared environments when required.</li> </ul> <h3>AI in the platform</h3> <ul> <li>Use <strong>AI and AI agents</strong> to accelerate environment setup, pipeline diagnosis, runbook generation, and operational automation.</li> <li>Explore and apply relevant AI infrastructure patterns (LLM gateways, observability for AI workloads, MCP/RAG/agents) where they improve how the team builds and operates.</li> </ul> <p><strong>How about you </strong></p> <div class="custom-field-control editable-field-control" data-type="long_text"> <div class="collapsed-field"> <ul> <li>At least <strong>7 years</strong> in a similar System Engineer / DevOps / Platform role running production workloads on public cloud (<strong>Azure preferred</strong>; AWS or GCP also welcome).</li> <li>Strong Linux skills; containerisation (<strong>Docker / containerd</strong>) — configuration, optimisation, monitoring, troubleshooting.</li> <li><strong>Kubernetes</strong> experience at a high level (<strong>AKS</strong> preferred / GKE or equivalent) — deploy, operate, debug.</li> <li>Observability: <strong>Prometheus, Grafana, OpenTelemetry</strong> (or equivalent) and a solid grasp of metrics / SLIs.</li> <li>Infrastructure as Code, config management, GitOps: <strong>Terraform, Helm, Argo CD</strong> (or equivalent).</li>