SRE Lead

Chubblifefund; Malaysia; On-site; MYR 250,000 - 420,000; Full time

Job summary

Chubblifefund is seeking a senior Site Reliability Engineering leader to define and drive the organisation's reliability strategy, bridging software development and operations through disciplined engineering. You will own production reliability, govern error budgets, and enforce readiness standards to protect business continuity.

You will build and scale a high-performing SRE team, embedding reliability into the SDLC, reducing toil through automation, and championing observability-led

Qualifications

• Degree in Computer Science, Software Engineering, IT or a related technical field.
• 8+ years’ experience in software engineering, platform reliability, or SRE, including 3+ years in people leadership.
• Strong hands-on coding ability in Python, Go, or similar, with automation experience.

Responsibilities

• Define and drive the SRE strategy and multi-year roadmap aligned to business priorities.
• Lead and develop the SRE team, including hiring, onboarding, performance management, career development, and succession planning.
• Own incident management, including severity classification, escalation, response SLAs, and leadership of major incidents.
• Champion blameless postmortems, root cause analysis, and implementation of systemic fixes.
• Establish and govern SLOs, SLIs, and error budgets, ensuring reliability targets align with business needs.
• Drive resilience engineering, including chaos engineering, GameDays, production readiness reviews, and failure mode analysis.

Skills

Python

Go

Leadership

Strategic thinking

Communications

Education

Degree in Computer Science/Software Engineering/IT

Tools

Dynatrace

Grafana

Prometheus

Splunk

ELK

Azure Monitor

Kubernetes

Terraform

OpenTelemetry

Job description

• Lead the Site Reliability Engineering function to define and drive the organisation’s reliability engineering strategy — bridging software development and operations through engineering discipline, not manual process.
• Own the end-to-end reliability posture of production systems: define SLO/SLI frameworks, govern error budgets, and enforce production-readiness standards to protect business continuity.
• Build, mentor, and scale a high-performing SRE team that prioritises engineering over toil — automating manual work, embedding reliability into the SDLC, and driving down mean time to recovery through systematic improvement.
• Champion observability-led engineering through full-stack Dynatrace adoption, AIOps integration, and data-driven reliability decision‑making at every layer of the stack.
• Serve as the primary reliability engineering partner to development and platform leadership, shaping architecture decisions, release policies, and automation strategy.

Key Responsibilities:

• Define and drive the SRE strategy and multi-year roadmap aligned to business priorities.
• Lead and develop the SRE team, including hiring, onboarding, performance management, career development, and succession planning.
• Own incident management, including severity classification, escalation, response SLAs, and leadership of major incidents.
• Champion blameless postmortems, root cause analysis, and implementation of systemic fixes.
• Establish and govern SLOs, SLIs, and error budgets, ensuring reliability targets are aligned to business needs.
• Drive resilience engineering, including chaos engineering, GameDays, production readiness reviews, and failure mode analysis.
• Reduce toil through automation, improved runbooks, and continuous operational improvement.
• Own observability and alerting standards, including monitoring strategy, dashboards, and alert quality.
• Partner with engineering, architecture, product, and leadership teams to embed reliability into design and delivery.
• Represent the SRE function in senior forums and provide reporting on reliability, risk, and operational performance.

Qualifications

• Degree in Computer Science, Software Engineering, IT, or a related technical field.
• 8+ years’ experience in software engineering, platform reliability, or SRE, including 3+ years in people leadership.
• Strong hands‑on coding ability in Python, Go, or similar, with experience building automation and self‑healing solutions.
• Proven experience leading enterprise‑scale SRE or platform reliability functions.
• Experience defining and operating RTO/RPO and SLI/SLO frameworks.
• Strong background in observability, production readiness, error budgets, and chaos engineering.
• Experience leading on‑call models, incident response, and executive stakeholder engagement.
• Solid understanding of SDLC, Agile, and DevOps delivery models.
• ITIL Foundation is desirable.

Managerial & Soft Skills:

• Proven people leader with experience building and coaching high-performing teams.
• Strategic thinker who can turn business priorities into reliability roadmaps.
• Strong communicator who can explain technical risk in business terms.
• Calm and decisive during major incidents.
• Influential partner across engineering, product, and leadership teams.
• Strong advocate for developer experience and sustainable on‑call practices.
• Data-driven and able to balance reliability, speed, and cost.
• Champions psychological safety, continuous learning, and operational excellence.

Technical Skills:

• Expert in Dynatrace, with experience in observability, monitoring, SLOs, tracing, and log management.
• Proficient in Grafana, Prometheus, Splunk, ELK, Azure Monitor, and Log Analytics.
• Strong knowledge of OpenTelemetry and telemetry pipeline design.
• Experience with ServiceNow, CI/CD tools, Kubernetes, Docker, Terraform, and Bicep.
• Familiar with Java, .NET, databases, APIs, Kafka, and cloud platforms, especially Azure.
• Experience with AIOps, AI-assisted triage, and automation tooling.
• Able to support reliability engineering through scripting, auto‑remediation, and operational automation.
• Experience in insurance or financial services.
• Dynatrace, Azure, ITIL 4, or Google Cloud/SRE‑related certifications.
• Experience with chaos engineering, AIOps, MLOps, and FinOps.
• Strong analytical skills and experience working with large operational datasets.