Negotiable
Undetermined
Onsite
London Area, United Kingdom
Summary: The Site Reliability Engineer (SRE) role in London focuses on automation, optimization, and process re-engineering for the Market Risk Platform, emphasizing the use of AI. The position aims to eliminate operational toil and enhance reliability operations, allowing existing SREs to concentrate on engineering rather than firefighting. Success is measured by the reduction of manual steps and improved recovery times. Candidates should possess strong Python skills and experience in agentic AI delivery.
Key Responsibilities:
- Build production-grade automation in Python to remove repetitive work.
- Create self-service capabilities for common requests.
- Implement “automation with Safety” including idempotency and rollback strategies.
- Map and redesign current operation processes to reduce waste and cycle time.
- Standardize runbooks/playbooks into executable workflows.
- Define and track operation KPIs related to toil and alert volume.
- Design and implement agentic workflows for diagnostics and remediation.
- Put strong controls in place for risky actions and productionize with monitoring.
Key Skills:
- Senior SRE experience on distributed systems and batch/intraday workloads.
- Strong Python programming skills.
- Experience with agentic AI and tool integration.
- Demonstrated process optimization abilities.
- Strong Linux and troubleshooting fundamentals.
- Experience with mixed estates including VMs and Cloud, with Kubernetes exposure.
- Exposure to Banking/Finance Market Risk Domains.
- Familiarity with the Athena ecosystem or similar.
Salary (Rate): undetermined
City: London
Country: United Kingdom
Working Arrangements: on-site
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Site Reliability Engineer
London, UK
Onsite 5 days
SRE Role description
We need an experienced SRE to focus predominantly on automation, optimization, and process re-engineering using AI for the Market Risk Platform. Success is measured by capacity created 9toil eliminated, fewer manual steps, faster recovery, safer/faster changes) not by being the primary BAU support resources. Strong Python and provable agentic AI delivery
Primary Objectives:
- Eliminate Operational toil and recurring manual work through durable automation
- Re-engineer support/change processes to reduce handoffs, approvals friction and rerun complexity
- Industrialize reliability operations so existing SREs spend less time firefighting and more time engineering
Key Responsibilities (Automation & Process first)
Automation Engineering (Core)
- Build production grade automation in Python(tools, services, workflows) to remove repetitive work: environment checks, dependency validation, automated reruns/reprocessing, safe restarts, drift detection, remediation actions, and standardized operation tasks
- Create self-service capabilities for common requests(guard railed, auditable, repeatable)
- Implement “automation with Safety”: idempotency, dry-run modes, approval gates where needed, rollback/undo strategies, and clear audit trails
Process Re-engineering (Core)
- Map current operation processes (incident/problem/change, release readiness, rerun/recovery, access/entitlements, environment onboarding) and redesign them to remove waster and reduce cycle time.
- Standardize runbooks/playbooks into executable workflows, reduce tribal knowledge via templates, checklists, and automated pre-flight controls
- Defined and track operation KPIs (toil hours removed, alert volume reduction, MTTR improvements, change failure rate reduction, rerun time reduction).
Agentic AI
- Design and implement agentic workflows that take action using tools/runbooks(e.g., diagnostics, evidence gathering, correlation, guided remediation, change-risk checks, automated rerun orchestration)
- Put strong controls in place: soped permissions, deterministic fallbacks, human-in-the-loop approvals for risky actions, evaluation harnesses and measurable outcomes.
- Productionize with monitoring, logging and post incident learnings feeding back into the agent/tooling
Observability (enablemen for automation)
Required skills & Experience
- Senior SRE experience on distributed systems and batch/intraday workloads in a production environment.
- Strong Python
- Provable agentic AI experience showing Tool integration, guard rails, evaluation approach
- Measurable impact (toil reduction, MTTR reduction, alert reduction etc)
- Demonstrated process optimization ability (removing steps/handoffs, standardizing workflows, implementing light weight controls with metrics)
- Strong Linux and troubleshooting fundamentals across application/system/network layers
- Experience working across mixed estates ( On Pre VMs + Cloud, with some Kubernetes exposure for operational monitoring/reruns)
Differentiators
- Exposure to Banking/Finance Market Risk Domains
- Experience and knowledge of Athena eco system familiarity or similar (Sec DB Quartz)