Application Reliability Engineer

KSTACK; São Paulo; Hybrid; BRL 180,000 - 320,000; Full time

Job summary

KSTACK is seeking an experienced Application Reliability Engineer to lead reliability improvements across critical applications, analyze recurring production issues, identify systemic weaknesses, and drive measurable gains in stability, resiliency, performance, observability, and operational effectiveness.

You will partner with engineering, operations, platform, infrastructure, and product teams to implement a practical roadmap for resilience, define RCAs, automate repetitive tasks, tune

Qualifications

• 8+ years in application reliability, production engineering, SRE, or application operations.
• Strong diagnostic skills across logs, metrics, traces, and distributed systems.
• Experience with incident management, RCA, and operational readiness.
• Hands-on experience with monitoring tools like Splunk, Datadog, New Relic, AppDynamics, Grafana.
• Strong understanding of application architecture, integrations, APIs, databases, and cloud platforms.
• Experience with automation (Python, Shell, Ansible, Jenkins, or similar).
• Excellent communication and stakeholder-management skills.
• Ability to lead cross-team reliability initiatives independently.

Responsibilities

• Lead reliability uplift initiatives across assigned applications and services.
• Assess current reliability posture: recurring incidents, degradation patterns, operational pain points, manual toil, and risk areas.
• Define and prioritise improvements that reduce incidents, customer impact, alert noise, and MTTR.
• Build a practical roadmap for resilience, availability, recoverability, and operational readiness.
• Evaluate operational procedures and identify gaps affecting responsiveness and production support.
• Partner with engineering, operations, platform, infrastructure, and product teams to execute the reliability plan.
• Lead production incident reviews for high-impact and complex issues.
• Perform deep-dive analysis to identify root causes, not just symptoms.
• Review logs, metrics, traces, dependency health, and post-incident findings to identify systemic failure patterns.
• Differentiate actionable incidents from duplicates or noisy alerts.
• Facilitate RCA, corrective actions, and preventive-action planning.
• Establish traceability for incidents, remediation items, owners, due dates, and decisions.
• Track remediation through completion and validate effectiveness.
• Improve incident-management workflows: triage, escalation, response, resolution, and communication.
• Identify repetitive manual tasks causing delays, inconsistencies, or operational risk.
• Recommend and drive automation for support activities, health checks, data collection, remediation steps, and reporting.
• Improve workflows to reduce manual effort and increase consistency.
• Define process improvements to enhance reliability, predictability, change readiness, and service support.
• Establish clear ownership and workflow visibility across teams.
• Evaluate applications for resiliency across dependencies, integrations, data flows, error handling, retry logic, timeouts, and recovery mechanisms.
• Recommend improvements to strengthen fault tolerance and reduce single points of failure.
• Assess behavior under degraded conditions and propose graceful-failure enhancements.
• Identify risks affecting reliability, availability, performance, or customer experience.
• Work with technical leads to embed reliability principles into enhancements and remediation work.
• Identify performance bottlenecks across application layers, integrations, and infrastructure.
• Recommend tuning strategies for throughput, latency, resource utilization, and scalability.
• Validate improvements through load testing, profiling, and performance diagnostics.
• Collaborate with engineering teams to ensure performance readiness for peak loads.
• Assess current monitoring and alerting effectiveness.
• Define meaningful health indicators, SLIs, SLOs, and error budgets.
• Reduce alert noise and improve signal-to-noise ratio.
• Strengthen end-to-end observability across logs, metrics, traces, dashboards, and synthetic monitoring.
• Ensure monitoring coverage for critical workflows, dependencies, and failure modes.
• Act as the reliability lead for cross-functional teams.
• Communicate reliability posture, risks, priorities, and progress to leadership.
• Coordinate remediation activities across engineering, operations, and product teams.
• Provide structured updates, dashboards, and reliability metrics to stakeholders.
• Drive accountability for reliability commitments and timelines.

Skills

SRE / production reliability

Incident management

RCA & post-incident analysis

Observability & monitoring

Diagnostics: logs metrics traces

Automation (Python, Shell)

Cloud platforms

Cross-functional leadership

Tools

Splunk

Datadog

New Relic

AppDynamics

Grafana

Job description

Role Overview

The Application Reliability Engineer will lead a structured reliability-improvement initiative across critical applications. The consultant will analyze recurring production issues, identify systemic weaknesses, and drive measurable improvements in stability, resiliency, performance, observability, and operational effectiveness.

This role requires a strong application-centric mindset, deep diagnostic skills, and the ability to convert operational noise into actionable reliability outcomes.

Key Responsibilities

Reliability & Production Stability

• Lead reliability uplift initiatives across assigned applications and services.


• Assess current reliability posture: recurring incidents, degradation patterns, operational pain points, manual toil, and risk areas.


• Define and prioritize improvements that reduce incidents, customer impact, alert noise, and MTTR.


• Build a practical roadmap for resilience, availability, recoverability, and operational readiness.


• Evaluate operational procedures and identify gaps affecting responsiveness and production support.


• Partner with engineering, operations, platform, infrastructure, and product teams to execute the reliability plan.

Incident Management, Analysis & Root Cause Resolution

• Lead production incident reviews for high-impact and complex issues.


• Perform deep-dive analysis to identify root causes, not just symptoms.


• Review logs, metrics, traces, dependency health, and post-incident findings to identify systemic failure patterns.


• Differentiate actionable incidents from duplicates or noisy alerts.


• Facilitate RCA, corrective actions, and preventive-action planning.


• Establish traceability for incidents, remediation items, owners, due dates, and decisions.


• Track remediation through completion and validate effectiveness.


• Improve incident-management workflows: triage, escalation, response, resolution, and communication.

Operational Automation & Process Improvement

• Identify repetitive manual tasks causing delays, inconsistencies, or operational risk.


• Recommend and drive automation for support activities, health checks, data collection, remediation steps, and reporting.


• Improve workflows to reduce manual effort and increase consistency.


• Define process improvements to enhance reliability, predictability, change readiness, and service support.


• Establish clear ownership and workflow visibility across teams.

Application Resiliency & Design Improvement

• Evaluate applications for resiliency across dependencies, integrations, data flows, error handling, retry logic, timeouts, and recovery mechanisms.


• Recommend improvements to strengthen fault tolerance and reduce single points of failure.


• Assess behavior under degraded conditions and propose graceful-failure enhancements.


• Identify risks affecting reliability, availability, performance, or customer experience.


• Work with technical leads to embed reliability principles into enhancements and remediation work.

Performance & Application Tuning

• Identify performance bottlenecks across application layers, integrations, and infrastructure.


• Recommend tuning strategies for throughput, latency, resource utilization, and scalability.


• Validate improvements through load testing, profiling, and performance diagnostics.


• Collaborate with engineering teams to ensure performance readiness for peak loads.

Monitoring, Alerting & Observability

• Assess current monitoring and alerting effectiveness.


• Define meaningful health indicators, SLIs, SLOs, and error budgets.


• Reduce alert noise and improve signal-to-noise ratio.


• Strengthen end-to-end observability across logs, metrics, traces, dashboards, and synthetic monitoring.


• Ensure monitoring coverage for critical workflows, dependencies, and failure modes.

Stakeholder Leadership & Communication

• Act as the reliability lead for cross-functional teams.


• Communicate reliability posture, risks, priorities, and progress to leadership.


• Coordinate remediation activities across engineering, operations, and product teams.


• Provide structured updates, dashboards, and reliability metrics to stakeholders.


• Drive accountability for reliability commitments and timelines.

Required Skills & Qualifications

• 8+ years in application reliability, production engineering, SRE, or application operations.


• Strong diagnostic skills across logs, metrics, traces, and distributed systems.


• Experience with incident management, RCA, and operational readiness.


• Hands-on experience with monitoring tools (e.g., Splunk, Datadog, New Relic, AppDynamics, Grafana).


• Strong understanding of application architecture, integrations, APIs, databases, and cloud platforms.


• Experience with automation (Python, Shell, Ansible, Jenkins, or similar).


• Excellent communication and stakeholder-management skills.


• Ability to lead cross-team reliability initiatives independently.

Preferred Qualifications

• Experience in large enterprise environments.


• Familiarity with ITIL processes.


• Experience with microservices, distributed systems, and cloud-native architectures.


• Prior consulting experience in reliability or production engineering.