DevOps Platform Engineer

Location: Canary Wharf, London (Hybrid, 2–3 days onsite)

About the Role

We are looking for a Senior DevOps / Platform Engineering specialist to support the reliability, resilience and operational performance of large-scale platforms within a regulated environment.

This role combines hands-on engineering with technical leadership, production incident management, automation and reliability engineering. You will drive improvements across platform operations, embed reliability throughout the software development lifecycle and apply agentic AI to incident, problem, change and risk management.

Key Responsibilities

• Take ownership of technical outcomes, drive engineering quality, mentor colleagues and share expertise across teams.
• Collaborate with product, platform, operations and security teams to embed reliability into the software development lifecycle.
• Define and track KPIs for reliability, performance and operational efficiency.
• Lead production incident management, including detection, triage, escalation and resolution, working with development and support teams.
• Manage major incident response for critical outages, ensuring rapid mitigation and clear stakeholder communication.
• Conduct blameless post-incident reviews and drive actionable follow-ups and systemic improvements.
• Establish runbooks, playbooks and operational readiness standards, continuously improving incident response processes and tooling.
• Drive AI-assisted incident and problem management, change management and risk management across ITSM activities.
• Automate operational processes, including incident response, failover, scaling and recovery.
• Implement self-healing mechanisms using auto-remediation, event-driven workflows and AI/ML-assisted operations where applicable.
• Implement Infrastructure as Code (IaC) and reduce manual effort through CI/CD pipelines, automated testing and deployment strategies such as blue/green and canary releases.
• Implement observability frameworks covering metrics, logs and traces, using appropriate monitoring and observability tools.
• Define and implement SLIs, SLOs, SLAs and error budgets across critical services.
• Apply resilient design patterns, including multi-region failover, active-active architectures, circuit breakers and bulkheads.
• Ensure platforms support high availability, fault tolerance and disaster recovery in line with financial market uptime requirements.
• Investigate platform failures, performance bottlenecks and systemic issues across complex, multi-tiered architectures.

Skills & Experience

• Proven technical experience in SRE, DevOps and/or Platform Engineering within large-scale, regulated environments.
• Deep technical expertise in on-premises and AWS cloud-native architecture and systems design.
• Strong implementation experience with observability tools and frameworks, including Prometheus, Grafana, OpenTelemetry, ELK/EFK stacks, CloudWatch, Datadog or similar.
• In-depth experience in incident management and production operations.
• Hands-on experience with CI/CD pipelines, Git, automation, scripting and Infrastructure as Code.
• Experience with Python, Go, Ansible, Terraform or similar tools.
• Demonstrable application of agentic AI engineering in observability, incident management and automated recovery.
• Strong understanding of networking, security and reliability engineering principles.
• Experience defining and implementing SLOs, SLIs and error budgets.
• Experience with AWS services such as EKS/ECS, Lambda, API Gateway, DynamoDB, Aurora and S3.
• Experience with SQL Server, Sybase and PostgreSQL, including Aurora.
• Experience supporting or developing applications using Unix/Linux, Java, C#/.NET and Python.
• Strong communication skills, with the ability to engage technical and non-technical stakeholders.
• A calm, decisive approach under pressure, with a hands-on problem-solving mindset and a focus on reliability and continuous improvement.

Preferred Experience

• Financial services or other data-intensive, regulated industries.
• Multi-region AWS architecture, high availability and mission-critical applications.
• Chaos engineering practices and resilience testing.
• AIOps and intelligent automation frameworks.