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Senior DevOps Engineer

Posted April 10, 2026
Full-time Mid-Senior Level

Job Overview

We are looking for an experienced Senior Cloud & DevOps Engineer to support the build and production readiness of an AI-powered analytics capability for a large enterprise client. This role will focus on establishing cloud infrastructure, CI/CD, environment management, deployment automation, monitoring, logging, and operational controls needed to take the solution through Dev, Test, and Production. The ideal candidate will have strong expertise in cloud-native architecture, infrastructure-as-code, release engineering, observability, and secure platform operations. This person will work closely with AI Engineers, Software Engineers, Data Engineers, and Data Scientists to ensure the solution is deployable, scalable, secure, and aligned with enterprise standards.

Responsibilities

  • Design and implement cloud infrastructure and deployment patterns for the solution in collaboration with client platform teams.
  • Build and maintain CI/CD pipelines to support repeatable, controlled releases across Development, Test, and Production environments.
  • Implement infrastructure-as-code for cloud resources, services, permissions, and environment configuration.
  • Support deployment of backend services, orchestration components, data services, and front-end applications.
  • Enable monitoring, logging, alerting, and telemetry for both platform health and end-user usage feedback loops.
  • Define and implement operational controls for reliability, performance, scalability, and incident response.
  • Support secure access patterns, secrets management, environment separation, and role-based controls.
  • Collaborate with engineering and AI teams to operationalise LLM-enabled workloads in a governed enterprise environment.
  • Ensure the solution aligns with architecture, security, and service transition requirements.
  • Support non-functional testing, release readiness, and path-to-production activities.
  • Contribute to support models, handover documentation, and internal enablement for ongoing operations.
  • Help define scalable platform patterns for future phases, including additional datasets and advanced AI capabilities.

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