Site Reliability Engineer (SRE)

Methodic; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Methodic is seeking an experienced Site Reliability Engineer to join our San Francisco on-site team. You will own monitoring, alerting, and self-healing workflows, ensuring reliability and scalability for our platform.

You will implement capacity planning, blue-green or canary deployments, and collaborate with software engineers to embed resilience by design. Expect on-call rotations and ongoing automation to reduce toil and improve performance.

Qualifications

• 5+ years in a Site Reliability Engineering or similar role.
• Strong coding/scripting abilities (Python, Go, or other) for building automation and tooling.
• Deep knowledge of systems monitoring and observability — experience with tools like Grafana, Datadog, Prometheus, etc., and the ability to interpret system metrics to spot problems.
• Understanding of high-availability design and distributed systems principles (load balancing, consensus, graceful degradation, etc.).
• Experience with incident management and a track record of improving systems based on lessons learned.
• Performance tuning experience — ability to use profiling and stress testing tools to find and fix bottlenecks.
• A collaborative mindset, capable of working with development teams to ensure reliability is built in from the start, not just after issues occur.

Responsibilities

• Develop and maintain advanced monitoring, alerting, and self-healing mechanisms that detect and address issues before they impact customers.
• Perform regular capacity planning and load testing to ensure the platform can scale ahead of demand without performance degradation (validating that we can sustain extremely high transaction rates per tenant).
• Improve deployment processes with strategies like blue-green or canary deployments to minimize risk and downtime during releases.
• Collaborate with software engineers to design resilient architectures – for example, build redundancy and failover capabilities into critical services (so that even if one component fails, the system remains operational).
• Participate in on-call rotations to respond to and resolve production incidents; lead blameless post-mortems to identify root causes and implement corrective actions.
• Automate routine operational tasks (from simple scripts to more complex tooling) to reduce manual work and error potential.
• Document reliability-related procedures and best practices, ensuring knowledge is shared and systems are well-understood by the team.

Skills

Python

Go

Scripting

Observability

Collaboration

On-call

Tools

Grafana

Datadog

Prometheus

Job description

Open role

Site Reliability Engineer (SRE)

San Francisco, CA (On-site)

Responsibilities

• Develop and maintain advanced monitoring, alerting, and self-healing mechanisms that detect and address issues before they impact customers.
• Perform regular capacity planning and load testing to ensure the platform can scale ahead of demand without performance degradation (validating that we can sustain extremely high transaction rates per tenant).
• Improve deployment processes with strategies like blue-green or canary deployments to minimize risk and downtime during releases.
• Collaborate with software engineers to design resilient architectures – for example, build redundancy and failover capabilities into critical services (so that even if one component fails, the system remains operational).
• Participate in on-call rotations to respond to and resolve production incidents; lead blameless post-mortems to identify root causes and implement corrective actions.
• Automate routine operational tasks (from simple scripts to more complex tooling) to reduce manual work and error potential.
• Document reliability-related procedures and best practices, ensuring knowledge is shared and systems are well-understood by the team.

Requirements

• 5+ years in a Site Reliability Engineering or similar role.
• Strong coding/scripting abilities (Python, Go, or other) for building automation and tooling.
• Deep knowledge of systems monitoring and observability — experience with tools like Grafana, Datadog, Prometheus, etc., and the ability to interpret system metrics to spot problems.
• Understanding of high-availability design and distributed systems principles (load balancing, consensus, graceful degradation, etc.).
• Experience with incident management and a track record of improving systems based on lessons learned.
• Performance tuning experience — ability to use profiling and stress testing tools to find and fix bottlenecks.
• A collaborative mindset, capable of working with development teams to ensure reliability is built in from the start, not just after issues occur.