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.
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
Site Reliability Engineering roles require participation in the on-call rotation, with support duty during and after business hours
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
Key Responsibilities & Deliverables
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
Team Collaboration
Availability for regular working sessions and discovery workshops with client teams
Ability to work independently while collaborating with client & Modus leaders
Overlap with client business hours daily is expected
Reliable high-speed internet is a must
Documenting solutions, sharing learnings with the team, contributing to internal wikis and runbooks
Pair program and collaborate on complex reliability and operational problems
Welcome code and architecture reviews; seek input on reliability designs
Ability to coordinate with security, platform, and development teams on reliability and operations
Bonus Skills
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
You’ll Love
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
