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# DevOps Engineer

- **Company:** Stott and May
- **Location:** London, UK
- **Salary:** £169,000.0
- **Contract:** Temporary contract
- **Skills:** Java (Programming Language), .NET Framework, Artificial Intelligence, Amazon Web Services, Amazon S3, Automation of Tests, C Sharp (Programming Language), Databases, Continuous Integration, Linux, DevOps, Disaster Recovery, Amazon DynamoDB, Fault Tolerance, Python (Programming Language), PostgreSQL, Microsoft SQL Server, Reliability Engineering, Ansible, Prometheus, Software Engineering, Datadog, Scripting, Grafana, Sybase, Software Application Programming, Git, Infrastructure Automation Frameworks, Deployment Automation, Hardware Infrastructure, Functional Programming, Cloudwatch, Api Gateway, Terraform, AIOps, Golang
- **Published:** October 15, 2026
- **Apply:** https://www.totaljobs.com/job/devops-engineer/stott-may-professional-search-limited-job108173123

## About the Role

Strong experience in SRE, DevOps, or Platform Engineering within large-scale, regulated environments.

 - Expertise in on-premise infrastructure and AWS cloud-native architecture.
 - Hands-on experience with AWS services including EKS/ECS, Lambda, API Gateway, DynamoDB, Aurora, and S3.
 - Observability tools such as Prometheus, Grafana, OpenTelemetry, ELK/EFK, CloudWatch, or Datadog.
 - Strong incident management, production support, and operational resilience experience.
 - Proficiency in CI/CD, Git, scripting, automation, and IaC tools such as Python, Go, Ansible, and Terraform.
 - Demonstrable experience applying agentic AI to observability, incident management, and automated recovery.
 - Strong understanding of networking, security, Linux/Unix, and reliability engineering.
 - Experience supporting or developing applications using Java, C#/.NET, Python, and databases including SQL Server, Sybase, and PostgreSQL/Aurora.

Desirable Experience

 - Financial services or other data-intensive, regulated industries.
 - Mission-critical applications and multi-region AWS architectures.
 - Chaos engineering, resilience testing, AIOps, and intelligent automation frameworks.

## Description

Lead production incident management, major incident response, root-cause analysis, and blameless postmortems.

 - Embed reliability practices across the software development lifecycle and define KPIs, SLIs, SLOs, SLAs, and error budgets.
 - Drive AI-assisted incident, problem, change, and risk management.
 - Automate operational processes, recovery, failover, scaling, and self-healing capabilities.
 - Implement Infrastructure as Code, CI/CD pipelines, automated testing, and deployment strategies.
 - Build and improve observability across metrics, logs, and traces.
 - Design resilient, highly available platforms with fault tolerance, disaster recovery, and multi-region capabilities.
 - Investigate complex platform failures, performance bottlenecks, and systemic reliability issues.