Site Reliability Engineer for fintech and regulated SaaS · AWS · Azure · Kubernetes · Observability · AIOps · Metro Manila, Philippines
I keep production systems up and make every change safe and auditable. SRE at a digital bank. Previously SRE and backend engineer at ING.
Available for remote SRE contracts · UTC+8 · Email me
- Recovered 130,000+ stuck transactional emails in 90 minutes, with none lost, during an SMTP outage. I tuned Postfix concurrency and worker allocation and worked through the queue in targeted batches.
- Eliminated intermittent 504s at the production ingress. I traced them to an ALB/Istio idle timeout mismatch and shipped a mesh-wide proxy fix through Terraform with zero downtime.
- Upgraded EKS with zero downtime through an automated two-phase rollout using Terraform and Karpenter disruption budgets.
- Responded to production alerts in a 3.7-minute median vs the team's 6.0 minutes across 277 alerts while on call for a legal tech SaaS platform.
- Ran 69 production changes through change management (38 deployments, 9 emergency changes), each with a change request and recorded outcome; about 6% rolled back safely.
- Expanded Dynatrace coverage and proactive alerting on critical banking services so incidents are caught earlier.
- Made Elastic Stack upgrades safe across 100+ nodes with Ansible tasks that check cluster health before applying changes. I also reordered shard allocation and node shutdown to stabilize DR exercises.
- Closed security findings: remediated flagged vulnerabilities across 100+ RHEL VMs and resolved all high-severity code-scan findings in three Go services.
- Azure DevOps pipeline watcher: monitors multi-hour deployment pipelines, classifies failed stages (timeout, transient, data validation, fatal), and auto-retries only the safe ones. It never reruns real migration errors.
- Salesforce ops agent: works cases, incidents, and change requests from a pasted link. Every write needs explicit human approval, enforced by tool permissions rather than instructions.
- Squadcast metrics pipeline: read-only API export that works within the 1,000-incident and 6-month limits, checks attribution against raw logs, and outputs aggregates only.
I use mental models, the latticework Charlie Munger describes, as everyday working tools. Where each one paid off:
| Model | How I applied it | Result |
|---|---|---|
| Inversion: ask how it fails, then prevent that | Listed how customer traffic could drop during EKS upgrades and capped node disruption per workload | Zero-downtime upgrades |
| First principles: fix the cause, not the symptom | Traced random 504s to mismatched ALB and Istio idle timeouts, fixed at the root mesh-wide | 100% of those errors gone |
| Second-order thinking: ask "and then what?" | Released 130,000 queued emails in controlled batches instead of all at once | All delivered in 90 minutes, none lost |
| Margin of safety: leave room for being wrong | AI ops tools can't write without human approval; upgrades run only after health checks pass | 100+ nodes upgraded safely |
| Checklists: make the safe path the default | Every production change followed the same plan, window, rollback, and recorded outcome | 69 changes, about 6% rolled back safely |
| The map is not the territory: check the source | Verified on-call attribution against raw logs before publishing any number | On-call numbers checked against raw logs |
I'm incredibly grateful to my mentor, Theron Bueno, for an insightful and inspiring six-month mentorship. Thank you for generously sharing your knowledge, not just on technical topics but also on essential soft skills like tailoring resumes, interview preparation, and confidence during an interview.
Christian Ortiz, Full-Stack Software Developer, mentored through ULAP.org
I started as one of ten ULAP.org cloud scholars in the Philippines. Today I mentor the next cohort.
A fixed-price 2-week reliability review: architecture walkthrough, a look at your alerts, incidents, and change process, then a written report ranking your top risks by business impact, plus fixes for the quick wins. Continue monthly if it's useful. Ask about a review
Site Reliability Engineer, Digital bank · Dec 2025 – present
AWS (EKS, EC2), Kubernetes, Karpenter, Istio, Terraform, Dynatrace, AWS DevOps Agent and AI-assisted operations, Postfix, GitLab CI
Site Reliability Engineer, ING Hubs Philippines · Dec 2024 – Dec 2025
Azure, RHEL, OpenShift, Elastic Stack (ELK), LGTM (Loki, Grafana, Tempo, Mimir), Ansible, disaster recovery planning and execution, capacity management, alert routing to Microsoft Teams
Backend Engineer, ING Hubs Philippines · Dec 2023 – Dec 2024
Java (Spring Boot, Vaadin), Node.js, Go, REST APIs, application security remediation
DevOps / Support Engineer (Contract), Legal tech SaaS company
On-call for an Azure-hosted SaaS platform used by law firms: resolved Squadcast alerts and production incidents, ran change requests in maintenance windows, deployed through Azure DevOps pipelines, managed access, and worked cases in Salesforce
Freelance Full-Stack Developer · Jan 2018 – Sep 2023
Built, deployed, and maintained web apps for 30+ clients with React, Next.js, Vue/Nuxt, and Node.js
| Area | Tools |
|---|---|
| Cloud and containers | Linux (RHEL), AWS (EKS, EC2), Azure, Kubernetes, OpenShift, Karpenter, Istio, Docker |
| Infrastructure as code | Terraform, Ansible |
| CI/CD | GitLab CI, GitHub Actions, Azure DevOps |
| Observability | Dynatrace, Elastic Stack (ELK), LGTM (Loki, Grafana, Tempo, Mimir) |
| Incident management | Squadcast, Salesforce |
| Languages | Python, Bash, Go, Java (Spring Boot), Node.js |
| AI and AIOps | AWS DevOps Agent, Claude, GitHub Copilot, Cursor |
AWS Certified Cloud Practitioner · Microsoft Azure Developer Associate (AZ-204) · Microsoft Azure Fundamentals (AZ-900) · Google IT Support Professional
- BS Computer Engineering, Pamantasan ng Lungsod ng Maynila (2023)
- Mentor at ULAP.org (2024 – present). I help early-career developers get their first engineering roles.