{ “@context”: “http://schema.org”, “@type”: “JobPosting”, “title”: “Site Reliability Engineer (Python)”, “description”: “
We need an experienced SRE to focus predominantly on automation, optimization, and process re‑engineering using AI for the Market Risk Platform. 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 waste 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: 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
- 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)
Company: Mphasis
Location: London
Job Description:
We need an experienced SRE to focus predominantly on automation, optimization, and process re‑engineering using AI for the Market Risk Platform. 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 waste 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: 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
- 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)
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Posted: April 28th, 2026