Site Reliability Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Site Reliability Engineer based in the United States.

Take ownership of the reliability, performance, and scalability of production systems supporting complex digital platforms and AI-powered applications. In this hands-on role, you will work alongside developers, platform engineers, and operations teams to build resilient infrastructure and prevent incidents before they affect users. You will oversee reliability across AWS infrastructure and Python backend services, establishing observability practices, service-level objectives, and effective incident response processes. Through automation, performance optimization, and continuous improvement, you will help teams move from reactive troubleshooting to proactive reliability engineering. You will also contribute to technical strategy, document operational best practices, and mentor engineers as the SRE function expands. This remote contract opportunity is ideal for an experienced reliability professional who enjoys solving challenging infrastructure problems and making a measurable impact on system availability and operational efficiency.

As Site Reliability Engineer, you will own critical aspects of production reliability, from infrastructure monitoring and incident management to automation, capacity planning, and engineering collaboration. Your responsibilities will include:

• Reliability engineering and observability: Design, implement, and maintain comprehensive observability systems covering metrics, logs, traces, alerting, and monitoring strategies aligned with business needs.

• Service-level objectives: Define and maintain service-level objectives (SLOs), service-level agreements (SLAs), and error budgets to establish clear reliability standards for backend services.

• Incident response and on-call support: Participate in a 24/7 Priority 0 (P0) on-call rotation, meeting a 10-minute acknowledgment service-level agreement. Validate and escalate AI-generated incident reports to the appropriate platform teams.

• Incident investigation: Troubleshoot production incidents, perform root-cause analysis, lead or contribute to postmortems, and implement corrective actions that reduce recurrence.

• AWS infrastructure management: Maintain and improve production infrastructure using AWS services such as Application Load Balancer (ALB), ECS/Fargate, RDS Aurora, Lambda, and IAM.

• Backend reliability: Debug, optimize, and improve Python services running in containers and serverless environments, focusing on availability, latency, throughput, and resource efficiency.

• Automation and toil reduction: Develop self-healing mechanisms and operational automation that reduce manual work, improve consistency, and increase engineering productivity.

• Performance and capacity planning: Analyze observability data to identify bottlenecks, forecast capacity requirements, optimize resource utilization, and improve system performance.

• Infrastructure and deployment practices: Review infrastructure changes and improve infrastructure-as-code, CI/CD pipelines, deployment automation, and release strategies.

• Reliability integration: Collaborate with development, security, platform, and operations teams to integrate reliability and observability throughout the software delivery lifecycle.

• AI workload operations: Support AI applications and services by addressing their operational requirements, reliability risks, and scaling needs.

• Technical documentation: Create and maintain runbooks, architecture documentation, troubleshooting guides, and operational procedures that enable teams to resolve issues independently.

• Technical leadership and mentoring: Help onboard and mentor additional SRE engineers as the team grows from approximately four engineers to a target of 8–12.

• Client and leadership collaboration: Participate in discovery workshops, regular working sessions, architecture reviews, and technical discussions, advising stakeholders on reliability trade-offs and operational strategy.

• Knowledge sharing: Document solutions, contribute to internal knowledge bases, pair program on complex challenges, and promote consistent reliability practices across teams.

Requirements:

The ideal candidate brings substantial hands-on experience in reliability, DevOps, or platform engineering, combined with strong software troubleshooting skills and the ability to collaborate effectively in distributed teams. The following qualifications are required:

• At least 6 years of hands-on experience in Site Reliability Engineering, DevOps, or Platform Engineering in production environments at scale.

• Deep expertise in AWS, including ALB, ECS/Fargate, RDS Aurora, Lambda, and IAM.

• Production-level Python backend engineering experience, including debugging and optimizing services deployed in containers and serverless environments.

• Experience establishing or building an SRE program from the ground up.

• Practical experience with incident response, on-call rotations, root-cause analysis, postmortems, and service-level objectives.

• Strong knowledge of observability systems, including metrics, logging, distributed tracing, monitoring, and alerting.

• Solid understanding of containerization technologies such as Docker and Kubernetes.

• Experience writing and maintaining infrastructure-as-code using tools such as Terraform, CloudFormation, or Pulumi.

• Hands-on experience with CI/CD pipelines, deployment automation, and modern release strategies.

• Demonstrated ability to troubleshoot distributed systems and investigate complex production failures.

• Proficiency in scripting with Python, Bash, or Go, alongside sound Linux/Unix administration fundamentals.

• Experience with Git, collaborative development workflows, and infrastructure automation patterns.

• Strong analytical and problem-solving skills, with the ability to identify reliability risks and implement sustainable solutions.

• Clear communication skills and the ability to explain technical decisions and reliability trade-offs to both engineering teams and business stakeholders.

• Ability to work independently while collaborating closely with client teams and technical leadership.

• Availability to participate in on-call support during and outside standard business hours, including the required 24/7 P0 rotation.

• Ability to overlap with client business hours daily and participate in regular working sessions and discovery workshops.

• Reliable, high-speed internet suitable for remote engineering work.

Preferred qualifications:

• Experience designing or operating internal developer platforms.

• Familiarity with chaos engineering, resilience testing, and failure scenario planning.

• Knowledge of cloud security, security hardening, compliance, and audit readiness.

• Experience operating AI infrastructure, large language model (LLM) serving environments, or agentic systems.

• Experience mentoring junior engineers or leading technical design discussions.

• Familiarity with cloud cost optimization and FinOps practices.

• Experience validating AI-generated incident reports and developing associated review workflows.

• Advanced Python performance tuning and backend optimization skills.

• Experience building SRE programs in high-growth or rapidly scaling environments.

Benefits:

• Employment type: Remote contract position.

• Opportunity to work with modern cloud infrastructure, including AWS, Kubernetes, infrastructure-as-code, and advanced observability platforms.

• Direct impact on production uptime, system performance, reliability, and operational efficiency.

• Exposure to the operational challenges of AI-powered applications and services.

• Opportunities to solve complex infrastructure and distributed systems problems.

• Collaboration with experienced developers, platform engineers, operations specialists, and client leadership.

• Opportunities to mentor engineers, contribute to technical strategy, and help shape reliability engineering practices.

• A continuous improvement culture that values learning from incidents, sharing knowledge, and celebrating team achievements.

• Compensation: Monthly gross salary expectations are requested in USD during the application process; a specific salary range is not provided in the posting.

• Location: The listing identifies Nigeria as the role location and describes the position as remote. Candidates should confirm country eligibility and work authorization requirements during the application process.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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