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AI Summary
Own and extend the GitOps deployment model and CI/CD pipelines for a real-time call-intelligence platform on AWS. Manage the observability stack, incident response practices, and security tooling to ensure platform reliability and scalability.
This is a remote position.
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Company Overview
Full Scale is a tech services company that helps businesses build dedicated teams of skilled software engineers. We make finding and retaining experienced software talent easy and affordable.
Position Summary
We are looking for a Senior DevOps Engineer to join our growing team and own the delivery pipeline and runtime health of every service on a production platform for a US-based client in the automotive retail space. The platform is a real-time call-intelligence system — telephony events flowing through event-driven middleware into a CRM, with a screen-pop that surfaces customer context to the advisor before they pick up the phone — built on a multi-account AWS foundation managed entirely as code. This is not a legacy shop being modernized. The platform is already serverless-first, GitOps-driven, and built for scale. You will own the CI/CD systems, the observability stack, and the incident response practices that keep a real-time, revenue-touching platform fast and reliable. You will work alongside an AWS Architect (who designs the platform) and a Data Scientist (who deploys ML models and voice agents) to make it all shippable, monitorable, and recoverable.
We are looking for a Senior DevOps Engineer to join our growing team and own the delivery pipeline and runtime health of every service on a production platform for a US-based client in the automotive retail space. The platform is a real-time call-intelligence system — telephony events flowing through event-driven middleware into a CRM, with a screen-pop that surfaces customer context to the advisor before they pick up the phone — built on a multi-account AWS foundation managed entirely as code. This is not a legacy shop being modernized. The platform is already serverless-first, GitOps-driven, and built for scale. You will own the CI/CD systems, the observability stack, and the incident response practices that keep a real-time, revenue-touching platform fast and reliable. You will work alongside an AWS Architect (who designs the platform) and a Data Scientist (who deploys ML models and voice agents) to make it all shippable, monitorable, and recoverable.
Key Responsibilities
- Own and extend the GitOps deployment model — OpenTofu/Terragrunt for infrastructure, GitHub Actions and AWS CodePipeline for application delivery — across all environments and AWS accounts.
- Maintain OIDC federation for deployment identity; enforce the zero long-lived-credentials standard across every pipeline and runner.
- Build and maintain deployment pipelines for AWS Lambda services, API Gateway configurations, containerized workloads on EKS/ECR, and the PWA front end.
- Implement progressive delivery for the real-time call path: canary and blue/green releases, automated rollback on error-rate or latency regression, and feature flags for risky changes.
- Manage EAS build and over-the-air update pipelines as React Native/Expo mobile and kiosk surfaces come online.
- Own the observability stack — CloudWatch, X-Ray, structured logging, metrics, and alerting — with particular attention to the WebSocket screen-pop path and the voice agent's prefetch cache.
- Define and instrument SLOs for the call-intelligence path. Screen-pop time-to-first-render and voiceagent lookup latency are the two numbers that matter most; own them.
- Build runbooks and on-call rotation practices. Lead incident response and blameless post-incident reviews; drive corrective actions to completion.
- Monitor and tune Redis caching, Aurora Serverless scaling behavior, and Lambda cold-start characteristics on latency-sensitive endpoints.
- Operationalize defense-in-depth tooling: GuardDuty, Security Hub, Inspector, Macie, WAF/Shield, orgwide CloudTrail, and automated EventBridge remediation.
- Own secrets management (AWS Secrets Manager / Parameter Store) and rotation for DMS, CRM, telephony, and payment integrations.
- Integrate security scanning into the pipeline: dependency scanning, container image scanning, IaC policy checks, and secret detection on commit.
- Support PCI-relevant controls on the secure payment link path and PII-handling controls across voice and call-intelligence services.
- Track and report AWS spend by account, service, and workload; identify and implement optimization (right-sizing, Savings Plans, Spot for appropriate workloads, S3 lifecycle policies).
- Provide capacity guidance ahead of new business-unit onboarding.
Requirements
- 4+ years in a DevOps, SRE, or Platform Engineering role with production ownership.
- Deep, hands-on AWS experience — Lambda, API Gateway, ECS/EKS, ECR, S3, Aurora, VPC networking, IAM.
- Strong Terraform or OpenTofu skills, including module design and multi-environment patterns. Terragrunt experience strongly preferred.
- Proven CI/CD ownership with GitHub Actions, CodePipeline, or equivalent.
- Container fluency: Docker, and Kubernetes on EKS (Fargate and/or managed node groups).
- Scripting and automation in Python and/or Node.js — enough to write real tooling, not just glue.
- Practical observability experience: you have designed alerts people actually trust, not just dashboards.
- Incident response experience in a system where downtime had immediate business consequences.
Nice to Have
- Experience with real-time systems — WebSockets, event-driven architectures, telephony/CPaaS integrations like 3CX, Twilio, or similar.
- AWS multi-account governance experience — Organizations, Control Tower, SCPs, IAM Identity Center, Transit Gateway.
- Exposure to PCI DSS or comparable compliance regimes.
- Automotive retail, DMS integration, or dealership technology background.
- AWS certification (DevOps Engineer – Professional, Solutions Architect – Associate or above).
Benefits
Why join us:
- Fully remote – work from anywhere in the Philippines.
- Work on a mature, serverless-first, GitOps-driven platform — not a legacy modernization project.
- Hands-on collaboration with senior architects and data scientists on a small, high-autonomy team.
- Opportunity to shape the operational practices of a platform that scales to multiple business units.
- Documentation-first culture with implementation-level detail over slideware.
- A team environment that values ownership, technical depth, and follow-through.
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