SRE Support Engineer - Observability
While this position is not currently open, we are interviewing strong candidates for upcoming opportunities on this team.
Location:Remote | Time Zone: (US, Canada, Brazil, Chile, Colombia, Mexico) (8AM–5PM Pacific)
Freedom to grow. Power to deliver.
Virtasant is a global technology services company delivering large-scale cloud, data, and engineering solutions across 130+ countries. We partner with some of the world’s largest organizations to help them build, operate, and scale internal platforms used by tens of thousands of engineers.
For this role, you will be supporting one of the most advanced internal developer platforms in the world, powering products used by hundreds of millions of people. The problems you will solve are deep, complex, and essential to keeping a global-scale organization moving.
Role Overview
The Observability & Tools Support Engineer provides high-impact technical support for customers of a large technology company’s internal IaaS platform, with a focus on monitoring, alerting, telemetry, and operational tooling.
This role spans a wide range of support—from white-glove onboarding and end-to-end customer enablement, to deep technical troubleshooting across Linux, networking, and observability systems (especially Prometheus and AlertManager). You will also contribute to improving the support function itself: strengthening tooling, documentation, workflows, and feedback loops so the service scales.
Success depends on excellent troubleshooting, strong written communication, comfort working with highly technical customers, and the maturity to identify patterns and drive operational improvements beyond individual ticket resolution.
Business Outcome
Become a trusted frontline expert for the customer’s observability ecosystem and operational tooling - delivering fast, accurate support across Slack and tickets, improving monitoring reliability, and reducing incident impact through better triage, troubleshooting, onboarding, and knowledge capture.
Success Measures
Healthy volume of threads and tickets handled with high-quality outcomes
Consistent achievement of time-based SLAs
High customer satisfaction through surveys
Accurate classification of issue type, severity, and recurring patterns
Reduced repeat issues through better docs, tooling, and scalable onboarding
What Will Be True When You Succeed
Customers can onboard smoothly to monitoring/alerting with minimal friction
Monitoring and alerting issues are resolved quickly, with fewer escalations
Linux and networking-related incidents reach resolution faster due to strong troubleshooting and clean handoffs
Engineering and SRE teams receive clear, actionable feedback based on real customer trends
Knowledge base content prevents tickets and accelerates self-service
Core Work Units
1) Frontline Support for Observability & Tooling
Manage Slack threads and tickets (roughly 50/50)
Handle a broad range of customer support: simple issue resolution through end-to-end onboarding
Provide clear, structured guidance to highly technical customers
Maintain strong attention to detail while managing multiple interactions in parallel
2) Deep-Dive Troubleshooting & Incident Support
Troubleshoot, isolate, and resolve monitoring and alerting issues (especially Prometheus + AlertManager)
Troubleshoot complex Linux and networking issues (TCP/IP fundamentals required)
Support OpenTelemetry, tracing, and telemetry pipelines, including investigation of gaps in signals and instrumentation
Drive incidents to resolution in partnership with Engineering/SRE teams
3) Documentation & Knowledge Development
Build and maintain customer-facing and internal knowledge base articles
Create informational posts for the community support platform
Turn repeated issues into reusable guides, checklists, and onboarding playbooks
4) Trend Analysis & Feedback to Engineering
Analyze and categorize customer interaction trends
Provide accurate, meaningful feedback to Engineering and SRE orgs to improve product/tooling
Identify “top offenders” and propose practical fixes (tooling, docs, process, product)
5) Operational Excellence & Continuous Improvement
Participate in post-mortem reviews and drive follow-through on improvements
Contribute meaningfully to team objectives and goals (process, tooling, and service scaling)
Bring creativity and discretion to resolve highly complex issues “outside the box”
High-Quality Work - what top performance looks like
Frontline Support
Moves smoothly from triage to deeper analysis without losing the customer
Communicates clearly and confidently with technical users
Maintains clean follow-ups and thread hygiene even with high context switching
Troubleshooting
Rapidly isolates issues across monitoring/alerting configs, Linux runtime behavior, and network connectivity
Uses structured approaches to incident handling: hypothesis → test → evidence → resolution
Produces high-signal writeups that accelerate downstream resolution
Documentation & Enablement
Documentation is clear enough that customers avoid opening tickets
Onboarding flows reduce time-to-value and prevent common misconfigurations
Captures “tribal knowledge” quickly and makes it reusable
Operational Excellence
Obsessing over details: correct severity, accurate tagging, clean timelines, strong handoffs
Spots patterns early and proactively proposes improvements that scale support
Typical Day / Work Patterns
~50% Slack support, ~50% ticket handling
Deep-dive investigations during lower ticket volume periods
Documentation writing and lightweight tooling/process improvements when patterns emerge
Weekly team review of escalations, themes, and operational improvements
High rate of context switching and parallel issue management
Required Skills & Experience (Non-Negotiable)
Several years supporting highly scalable applications and web services
Hands-on experience with open-source observability and cloud-native tooling, including:
Kubernetes (and container fundamentals)
Prometheus and AlertManager troubleshooting
OpenTelemetry and distributed tracing concepts
Strong understanding of the Linux operating system (command line, process/network debugging, logs)
Good understanding of infrastructure observability principles (signals, alerting strategy, SLO thinking, noise reduction)
Good understanding of the TCP/IP suite and practical networking troubleshooting
Strong experience troubleshooting ambiguous, multi-layer issues
Excellent analytical capability and strong attention to detail
Strong written and verbal communication (clear, structured, customer-friendly)
Comfortable working with a very technical customer base
Passion for Technical Support and a service mindset
Nice-to-Haves
Experience improving or supporting internal support tooling or workflows (automation, templates, runbooks)
Experience operating at scale in a services environment (pattern detection, KPI/SLA awareness, operational process maturity)
Familiarity with Grafana, log aggregation, incident tooling, and production support practices
Prior SRE or platform support experience
Minimum Qualifications
3–7+ years in Technical Support Engineering, SRE support, DevOps, Platform Support, or similar
Demonstrated experience supporting distributed systems, IaaS, or cloud platforms
Strong Linux, troubleshooting, and customer-facing communication background
Evidence of documentation, knowledge-base contributions, and process improvement mindset
Disqualifiers: weak Linux fundamentals, inability to troubleshoot systematically, poor written communication, or discomfort supporting highly technical users.
What You’ll Love
Real technical problem solving with tangible customer impact
A role that blends deep troubleshooting with scaling support via docs, tooling, and process
High autonomy in a remote-first environment
What May Be Challenging
High context switching and managing multiple threads in parallel
Repeated patterns that require discipline to convert pain into scalable improvements
Supporting high-visibility systems where speed and accuracy matter
Differentiation
Industry: Remote-first, trust-based culture; global team; autonomy; modern systems; meaningful technical challenges
Internal: High-impact, customer-facing observability support; direct influence on tooling and process maturity; opportunity to shape scalable support practices
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