Job description template

Application Support Engineer

As an Application Support Engineer, you’ll own the health of customer-facing and internal applications by triaging incidents, driving troubleshooting to resolution, and partnering with engineering to prevent repeat issues. You’ll balance fast response with strong documentation and monitoring practices so systems stay stable and users experience minimal disruption.

Responsibilities

Monitor application and service health using dashboards, logs, and alerts; investigate anomalies and rising error rates
Triage incidents based on customer impact, logs, and metrics; coordinate next steps and ensure timely resolution
Perform root-cause analysis for production issues and document findings, timelines, and remediation actions
Manage and execute incident communications with internal stakeholders, including clear status updates and mitigation details
Work with engineering teams to implement fixes, improve observability, and reduce future failures
Create and maintain runbooks, knowledge base articles, and operational documentation for supported services
Support release and change activities by validating deployments, watching for regressions, and escalating risks early

Must-have qualifications

Hands-on experience troubleshooting and resolving production incidents using logs, metrics, and traces
Ability to perform root-cause analysis and translate findings into actionable prevention steps
Experience creating and maintaining runbooks and operational documentation for supported applications
Strong understanding of HTTP/web application behavior, APIs, and common failure modes (timeouts, retries, caching, auth)
Proficiency with at least one scripting language (e.g., Python, Bash, PowerShell) to analyze logs or automate routine support tasks
Experience working with ticketing/incident management tools to track issues from triage through closure

Nice to have

Experience supporting applications hosted on AWS or another major cloud platform
Familiarity with monitoring/alerting tooling (e.g., Datadog, Grafana, Prometheus, ELK) and designing useful alerts
Experience with containerized deployments (e.g., Docker) and debugging runtime issues

What success looks like in 12 months

Reduce incident recurrence
Improve mean time to acknowledge and resolve
Strengthen observability and alert quality
Raise operational readiness
Increase change safety

Logistics

Full-time (40 hours a week), remote from Latin America.
Working hours overlap with US business hours.

About the company

[About your company: what you build, your stage and team size]

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Interview scorecard

Score every candidate against the same bar

Deliver reliable application operations by resolving incidents quickly, preventing recurrence, and improving observability and documentation for supported services.

Outcomes to measure

What this hire should deliver in the first year. Replace [N] with your own targets.

Reduce incident recurrence. Measure: reduce repeat production incidents by [X]% over 12 months through root-cause-driven prevention
Improve mean time to acknowledge and resolve. Measure: improve time to acknowledge by [X]% and time to resolve by [X]% for incidents in supported applications
Strengthen observability and alert quality. Measure: eliminate [X] top alert noise sources and add [N] monitoring improvements that lead to earlier detection
Raise operational readiness. Measure: create or update [N] runbooks and complete documentation coverage for [X]% of critical supported services
Increase change safety. Measure: support [N] releases/change events with documented validation steps and achieve [X]% successful post-deploy monitoring outcomes without unplanned rollback escalations

Competencies and weights

What to evaluate, how much it counts and what a strong answer looks like.

Incident Troubleshooting · 29%
The role is centered on quickly identifying causes, mitigating impact, and restoring service using production signals. Evaluated in Round 1.

Weak: Identifies only symptoms and needs repeated guidance to propose next steps
Meets the bar: Uses logs/metrics to narrow the fault domain and proposes a credible mitigation plan
Strong: Rapidly correlates signals (logs/metrics/traces) to isolate root causes and drives resolution with minimal back-and-forth

Root Cause Prevention · 19%
Support success depends on turning incidents into lasting improvements that reduce recurrence. Evaluated in Round 2.

Weak: Documents events but prevention actions are vague or not linked to the cause
Meets the bar: Produces a clear root cause and maps it to specific prevention work
Strong: Leads cross-team prevention that measurably reduces repeat incidents or alert noise

Operational Documentation · 16%
Accurate runbooks and knowledge base content improve response consistency and onboarding. Evaluated in Round 2.

Weak: Runbooks are incomplete, outdated, or don’t include decision criteria
Meets the bar: Runbooks include symptoms, diagnostics, escalation paths, and safe remediation steps
Strong: Documentation is structured for fast execution, kept current, and improves time-to-resolution for multiple incident types

Web and API Reliability · 15%
Understanding web/API failure modes is essential for effective triage and mitigation. Evaluated in Round 1.

Weak: Troubleshoots without referencing HTTP/API behaviors or common reliability pitfalls
Meets the bar: Connects issues to likely HTTP/API causes (auth, caching, timeouts, retries) and validates with evidence
Strong: Systematically tests hypotheses using request/response patterns and understands interaction effects across services

Automation and Scripting · 11%
Scripting increases support efficiency and improves analysis quality during high-volume events. Evaluated in Round 3.

Weak: Relies on manual steps and struggles to create repeatable scripts
Meets the bar: Writes straightforward scripts to parse logs/metrics or automate routine checks
Strong: Builds safe, reusable tooling that speeds investigations and reduces human error

Ticketing and Ownership · 10%
Independently tracking work from triage through closure ensures reliable execution and stakeholder trust. Evaluated in Round 3.

Weak: Tickets stall, status updates are unclear, or closure criteria are missing
Meets the bar: Manages tickets end-to-end with clear updates, evidence, and closure quality
Strong: Proactively identifies risks, escalates appropriately, and ensures accurate documentation of decisions

Interview questions

Questions for every interview round

Each round has an owner, a time box and questions that test the competencies above.

Round 1: Incident triage and reliability fundamentals
Support Engineering Lead · 60 min

Tell me about a production incident you handled end-to-end. How did you use logs and metrics to narrow scope and decide on the first mitigation step?
Walk through how you would diagnose a sudden rise in HTTP 5xx errors for a specific API endpoint. What signals would you check first and why?
Describe a time you identified an issue caused by retry behavior, timeouts, caching, or authentication. How did you confirm the cause and prevent it?
What would you do if you had incomplete observability during a live incident—how would you still make progress safely?

Round 2: Root cause, prevention, and documentation
Site Reliability or Engineering Partner · 60 min

Describe a root-cause analysis you performed for a recurring issue. What was the cause, and what specific prevention actions did you drive?
Give an example of how you turned incident learnings into an improved runbook. What sections did you add or change to speed future response?
How do you decide which issues should become prevention work versus quick fixes? Share a real example and the reasoning behind it.
Tell me about a prevention improvement (monitoring, workflow, configuration, or code change) that reduced repeat incidents or alert noise. What evidence showed it worked?

Round 3: Automation, ownership, and execution quality
Application Support Manager · 60 min

Describe a script or automation you built to help with support work (e.g., log parsing, report generation, health checks). What problem did it solve and how did you validate correctness?
Tell me about a time you owned tickets from triage to closure with multiple stakeholders. How did you manage updates, evidence, and handoffs?
What is your approach to release/change support to catch regressions early? Share how you would document validation steps and escalation triggers.
Describe a scenario where you had to balance speed and safety during an incident. What trade-offs did you make and how did you decide?

Red flags to watch for

Repeated examples where incidents were resolved but root causes were not identified or prevention actions were not taken
Vague or incomplete incident narratives (no evidence from logs/metrics, unclear decision criteria, or missing timelines)
Low evidence of documentation hygiene (runbooks missing key diagnostics/escalation steps or frequently outdated content)
Difficulty expressing how web/API reliability behaviors (timeouts, retries, caching, auth) map to observed failures
Automation examples that are unsafe, unreliable, or not validated for correctness

How much does it cost to hire an Application Support Engineer in Latin America?

In 2026, a senior Application Support Engineer in Latin America costs $6,750 to $7,750 a month all-in, versus $14,625 in the US: up to 54% less. Mid-level starts at $4,500.

Country

Mid-level

Senior

Argentina

$4,500

$6,750

Brazil

$5,000

$7,500

Colombia

$4,500

$6,750

Mexico

$5,250

$7,750

United States

$11,875

$14,625

Monthly cost in USD, all-in: the talent's salary plus Teilur's flat 20% fee, from our 2026 rates. The United States row shows what the same role typically costs there.

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Frequently asked questions

What does an Application Support Engineer do?

Typical responsibilities include: monitor application and service health using dashboards, logs, and alerts; investigate anomalies and rising error rates; triage incidents based on customer impact, logs, and metrics; coordinate next steps and ensure timely resolution; perform root-cause analysis for production issues and document findings, timelines, and remediation actions. The full list is in the template above.

How much does it cost to hire an Application Support Engineer in Latin America?

In 2026, a senior Application Support Engineer in Latin America costs $6,750 to $7,750 a month all-in, versus $14,625 in the US: up to 54% less. Mid-level starts at $4,500.

Can I customize this Application Support Engineer job description?

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Application Support Engineer Job Description Template