Site Reliability Engineer Engineer at Modus Create in Brazil; Colombia; Costa Rica; Mexico; United States of America

Job description

• We are seeking an experienced Site Reliability Engineer to build reliable, observable systems that enable client teams to operate with confidence at scale. You'll work embedded within cross-functional teams—partnering with developers, platform engineers, and operations teams—to reduce toil, improve system reliability, and prevent incidents before they impact users.
• As a Senior Site Reliability Engineer, you take ownership of system reliability across our full backend stack—from AWS infrastructure (ALB, ECS/Fargate, Aurora) to Python services. You design and maintain observability systems, define SLAs and error budgets, build incident response processes, and drive improvements in uptime and performance. You'll participate in 24/7 P0 on-call rotations with a 10-minute acknowledgment SLA, lead incident investigations and postmortems, and help teams shift from reactive firefighting to proactive reliability engineering. You'll also mentor and onboard additional SRE engineers as the team scales from 4 to 8-12 over the coming months.
• The Site Reliability Engineer will work shoulder-to-shoulder with cross-functional teams to ensure systems remain resilient, scalable, and observable across client environments. You'll also have opportunities to advise leadership on reliability strategy and help shape how organizations approach operational excellence.

Responsibilities

• Design observability systems (metrics, logging, tracing) and define SLOs, error budgets, and monitoring strategies aligned with business needs
• Own 24/7 P0 on-call rotation with 10-minute acknowledgment SLA; validate and escalate AI-generated incident reports to platform teams
• Establish reliability standards and SLA targets for backend services
• Mentor and onboard additional SRE engineers as team scales to 8-12
• Participate in incident response, troubleshooting, root-cause analysis, and postmortems
• Implement reliability improvements, capacity planning, and performance optimization
• Build self-healing automation and toil-reduction initiatives to minimize manual operational work
• Collaborate with teams to integrate reliability and observability into delivery
• Support modern workloads including AI applications and services; understand their operational and reliability requirements
• Create runbooks, architecture documentation, and troubleshooting guides to enable independence
• Review infrastructure changes and contribute to reliability standards and consistency
• Actively tune systems for latency, throughput, and resource efficiency based on observability data

Requirements

• 6+ years hands-on experience in SRE, DevOps, or Platform Engineering at scale
• Strong proficiency in one cloud platform: Deep AWS expertise (ALB, ECS/Fargate, RDS Aurora, Lambda, IAM)
• Production Python backend engineering experience; comfortable debugging and optimizing Python services in containers and Lambdas
• Experience building or bootstrapping SRE programs from scratch
• Hands-on experience with incident response, on-call rotations, postmortems, and SLOs
• Deep experience designing and implementing observability (metrics, logging, tracing, alerting)
• Solid understanding of containerization (Kubernetes, Docker) and deployment automation
• Experience writing and maintaining infrastructure-as-code (Terraform, CloudFormation, Pulumi, etc.)
• Hands-on experience with CI/CD pipelines and deployment strategies
• Ability to troubleshoot distributed systems and production issues with debugging complex failures
• Clear communication skills and the ability to explain reliability trade-offs to stakeholders
• Scripting proficiency (Python, Bash, Go); Linux/Unix administration fundamentals
• Version control (Git), collaboration workflows, and infrastructure automation patterns
• Experience designing or operating internal developer platforms
• Familiarity with chaos engineering, resilience testing, or failure scenario planning
• Cloud security and compliance experience (audit readiness, security hardening)
• Experience with AI infrastructure, LLM serving, or agentic system operations
• Mentoring junior engineers or leading technical design discussions
• Cost optimization and cloud FinOps practices
• Experience with AI-generated incident reports and validation workflows
• Python performance tuning and backend optimization
• Building SRE programs in high-growth or fast-scaling environments

Skills

Required

• Python
• Bash
• Go
• Kubernetes
• Docker
• Terraform
• CloudFormation
• Pulumi
• CI/CD pipelines
• Git
• Linux/Unix administration
• Incident response

Preferred

• Internal developer platforms
• Chaos engineering
• Resilience testing
• Cloud security
• Compliance
• AI infrastructure
• LLM serving
• Agentic systems

Benefits

• Learn from every incident and continuously improve systems
• Solve challenging reliability, observability, and operational problems
• Work with modern cloud platforms, Kubernetes, infrastructure-as-code, and observability
• Make a direct impact on system uptime, performance, and operational efficiency
• Collaborate with great teams and help shape enterprise reliability and SRE best practices
• Support teams operating AI applications and services reliably and safely at scale
• By joining our team, you'll be part of a winning squad that plays to each other's strengths and celebrates every success together