CW | Senior DevOps Engineer

About CBTW

CBTW is a global independent tech consultancy group. With a team of more than 3,000 talented tech specialists on the ground in over 35 cities across Europe, the USA, Asia, Australia and Africa, we serve clients of all sizes. We believe collaboration betters our world. Our unique open ecosystem model allows us to deliver end-to-end tech solutions.

About Our Partner

Our Partner is one of Australia's leading commercial credit-reporting and data businesses.

We help tens of thousands of businesses make smarter, faster credit decisions - powered by a modern data platform running on AWS. Our engineering teams ship continuously, and our DevOps team is the engine that lets them do it safely and at speed

About the role

We run a substantial production platform: dozens of containerised services on AWS ECS Fargate, a fleet of Aurora databases, a large multi-repo GitHub estate, and a Datadog-based observability stack. We're a deliberately lean, high-leverage DevOps team - we scale our impact through automation, strong self-service tooling, and AI rather than through headcount.

We're hiring a Senior DevOps Engineer to be a senior individual contributor across our platform agenda. This is not a ticket-queue role. You'll own meaningful slices of the platform end-to-end - driving cloud cost efficiency, making reliability measurable and enforceable, building self-service developer tooling and API infrastructure, and using agentic AI harnesses (including Claude Code and MCP) as a genuine force-multiplier in everyday operations. You'll set technical direction in your areas and raise the bar across a team that punches well above its size.

Cloud foundation - cost & risk

• Drive cost efficiency across a multi-account AWS environment: cost dashboards, budgets, right-sizing of compute and databases, log-volume reduction, storage lifecycle policies, and Savings Plan coverage.
• Eliminate platform risk by retiring end-of-life runtimes, simplifying over-engineered infrastructure, and consolidating accounts with consistent guardrails (SCPs) and tagging.
• Bring AI/Bedrock spend under governance with attribution and budgets.

Reliability as a product

• Extend SLO coverage across production services and manage SLOs and monitors as code in Terraform.
• Make error budgets actionable, cut alert noise, measure MTTD/MTTR, and integrate alerting cleanly into the incident-management workflow.
• Establish and run disaster-recovery drills with documented recovery objectives

Self-service developer platform

• Extend our reusable CI/CD workflows and golden-path service templates so new services reach production in hours, not days.
• Build out an internal developer platform (self-service deployments, ephemeral environments) and a production API Gateway for external APIs.
• Move secrets to runtime injection via AWS Secrets Manager, harden the container build pipeline, and consolidate infrastructure-as-code onto a single approach.

AI-augmented operations

• Build and maintain a library of reusable skills for our AI harness (pipeline fixes, incident analysis, cost optimisation, infrastructure generation) and roll out MCP servers that make ops data queryable by engineering teams.
• Apply agentic AI to incident root-cause analysis and IaC authoring, with sensible human in-the-loop guardrails.

Must have:

• 5+ years in DevOps / Platform / SRE / Cloud Engineering, with senior ownership of production systems.
• Deep AWS expertise - ECS/Fargate, RDS/Aurora (MySQL & PostgreSQL), Lambda, IAM, VPC, S3, CloudWatch, API Gateway - and comfort operating a multi-account AWS Organisation.
• Terraform at production scale: modules, workspaces, multi-environment, and code review discipline.
• CI/CD with GitHub Actions - reusable workflows, composite actions, and OIDC-based cloud authentication.
• Containers & Docker - building, securing, and operating containerised workloads.
• Observability - hands-on with Datadog (or Prometheus/Grafana/New Relic equivalents): APM, SLOs, monitors-as-code, and log/metric/trace pipelines.
• Cloud cost management (FinOps) - right-sizing, Savings Plans/RIs, and cost attribution through tagging.
• Reliability practice - SLOs, error budgets, on-call, blameless RCA, and MTTR/MTTD measurement.
• Strong scripting (Python and/or Bash) and the ability to work across a polyglot codebase (PHP, TypeScript, Python).
• Security-conscious by default: least-privilege IAM, secrets management, and WAF/GuardDuty/Security Hub-style controls.
• AI-augmented engineering - fluent with agentic coding harnesses (e.g. Claude Code) and MCP, building reusable skills and prompts to automate operational toil. You treat AI as a core part of your workflow, not an afterthought.
• Strong English communication skills, especially in the global software development environment

Nice to have:

• Built agentic workflows or custom MCP servers/tools that expose ops data (logs, metrics, infra) to AI harnesses.
• Experience building an internal developer platform or self-service tooling.
• API Gateway and external-API productionisation (rate limiting, usage metering).
• Blue-green / canary deployments (we use AWS CodeDeploy).
• Data-platform infrastructure - Databricks, dbt, MWAA/Airflow, EventBridge/SQS, or streaming architectures.
• Jira Service Management / Atlassian incident & problem management.
• Kubernetes (EKS) - including the judgement to know when not to reach for it.
• Significant migration experience (CI platform migrations, major database engine upgrades).

Due to the large number of applicants, only shortlisted candidates will be contacted.