Site Reliability Engineer

• We need to focus predominantly on automation, optimization, and process re-engineering using AI for our Market Risk Platform.
• We need to eliminate operational toil and recurring manual work through durable automation.
• We need to re-engineer support and change processes to reduce handoffs, approval friction, and rerun complexity.
• We need to industrialize reliability operations so our SREs spend less time firefighting and more time engineering.
• We need to build production-grade automation in Python to remove repetitive work such as environment checks, dependency validation, automated reruns or reprocessing, safe restarts, drift detection, remediation actions, and standardized operational tasks.
• We need to create self-service capabilities for common requests that are guard-railed, auditable, and repeatable.
• We need to implement automation with safety features such as idempotency, dry-run modes, approval gates where needed, rollback or undo strategies, and clear audit trails.
• We need to map current operational processes, including incident, problem, change, release readiness, rerun and recovery, access and entitlements, and environment onboarding, then redesign them to remove waste and reduce cycle time.
• We need to standardize runbooks and playbooks into executable workflows, reduce tribal knowledge through templates and checklists, and add automated pre-flight controls.
• We need to define and track operational KPIs such as toil hours removed, alert volume reduction, MTTR improvements, change failure rate reduction, and rerun time reduction.
• We need to design and implement agentic workflows that can take action using tools and runbooks for diagnostics, evidence gathering, correlation, guided remediation, change-risk checks, and automated rerun orchestration.
• We need to put strong controls in place, including scoped permissions, deterministic fallbacks, human-in-the-loop approvals for risky actions, evaluation harnesses, and measurable outcomes.
• We need to productionize solutions with monitoring, logging, and post-incident learnings feeding back into the agent and tooling.
• We need to enable observability for automation.

Technologies:

• AI
• Cloud
• Support
• Kubernetes
• LESS
• Linux
• Network
• Python
• Rails
• Java, We are hiring an experienced SRE for our Market Risk Platform in London, UK, with a 5-day onsite working arrangement. This is a contract inside IR35 or permanent opportunity, and we are looking for someone who can drive automation, optimization, and process re-engineering using AI. Success in this role is measured by capacity created, toil eliminated, fewer manual steps, faster recovery, and safer, faster changes. We are building durable improvements to our reliability operations, with a strong focus on Python, agentic AI, and measurable operational impact.

• We need at least 8 years of experience.
• We need senior SRE experience on distributed systems and batch/intraday workloads in a production environment.
• We need strong Python skills and experience with Python-based applications.
• We need proven agentic AI delivery experience, including tool integration, guard rails, evaluation approaches, and measurable impact.
• We need exposure to cloud technologies.
• We need strong Linux and troubleshooting fundamentals across application, system, and network layers.
• We need experience working across mixed estates, including on-prem VMs, cloud, and some Kubernetes exposure for operational monitoring and reruns.
• We value exposure to banking, finance, and market risk domains.
• We value familiarity with the Athena ecosystem or similar platforms such as SecDB and Quartz.
• We are hiring for work in London, UK, with a 5-day onsite arrangement.
• We are not providing visa sponsorship.