MercorCoding & software eval
Infrastructure / Site Reliability Engineer (SRE)
$200/hr
About this role, in Mercor's words
Mercor connects exceptional technical talent with leading organisations working on ambitious technology and AI initiatives. We are looking for experienced Infrastructure / Site Reliability Engineers (SREs) to join a full-time engagement focused on building and operating complex, enterprise-grade infrastructure. We are seeking engineers with strong hands-on experience building, operating, debugging, and scaling sophisticated production systems. The ideal candidate has worked extensively with Kubernetes, AWS, observability platforms such as Datadog, and modern infrastructure tooling .
What you'll do
- Build, operate, and improve highly available and scalable production infrastructure.
- Manage and optimise Kubernetes-based production environments .
- Design and maintain cloud infrastructure, primarily across AWS .
Show all 10 itemsHide the other 7 in What you'll do
- Improve system reliability, availability, scalability, and operational efficiency.
- Build and maintain observability across infrastructure and applications using Datadog or similar platforms.
- Investigate production incidents, perform root-cause analysis, and implement durable fixes.
- Improve monitoring, alerting, logging, tracing, and overall production visibility.
- Develop automation and internal tooling to reduce manual operational work.
- Partner closely with software engineering teams on deployments, infrastructure, and production reliability.
- Contribute to infrastructure architecture and technical decisions for complex distributed systems.
Quoted from selected sections of Mercor's posting. The full posting may state other conditions. Read the full posting
A closer look
More context, when you need it.
Full job descriptionThe original posting, in Mercor's words
Posted by Mercor, reproduced here so you can judge the role before clicking. Original posting ↗
Mercor connects exceptional technical talent with leading organisations working on ambitious technology and AI initiatives. We are looking for experienced Infrastructure / Site Reliability Engineers (SREs) to join a full-time engagement focused on building and operating complex, enterprise-grade infrastructure. We are seeking engineers with strong hands-on experience building, operating, debugging, and scaling sophisticated production systems. The ideal candidate has worked extensively with Kubernetes, AWS, observability platforms such as Datadog, and modern infrastructure tooling .
This is a full-time opportunity , and candidates must be able to commit to full-time engagement.
What You'll Do
• Build, operate, and improve highly available and scalable production infrastructure.
• Manage and optimise Kubernetes-based production environments .
• Design and maintain cloud infrastructure, primarily across AWS .
• Improve system reliability, availability, scalability, and operational efficiency.
• Build and maintain observability across infrastructure and applications using Datadog or similar platforms.
• Investigate production incidents, perform root-cause analysis, and implement durable fixes.
• Improve monitoring, alerting, logging, tracing, and overall production visibility.
• Develop automation and internal tooling to reduce manual operational work.
• Partner closely with software engineering teams on deployments, infrastructure, and production reliability.
• Contribute to infrastructure architecture and technical decisions for complex distributed systems.
Ideal Background
• Professional experience in Infrastructure Engineering, Site Reliability Engineering (SRE), Platform Engineering, DevOps, or Production Engineering .
• Hands-on experience operating complex, enterprise-grade production systems .
• Strong production experience with Kubernetes .
• Strong experience with AWS and cloud-native infrastructure.
• Experience with Datadog , Prometheus, Grafana, or comparable observability platforms.
• Experience with Infrastructure as Code using Terraform, Pulumi, or equivalent technologies .
• Strong understanding of distributed systems, networking, containers, Linux, and cloud architecture.
• Experience building or maintaining CI/CD and production deployment infrastructure.
• Strong debugging, troubleshooting, and incident-response capabilities.
• Proficiency in at least one programming or scripting language, such as Python, Go, or Bash .
Strong Signals
• Experience operating Kubernetes and cloud infrastructure at significant production scale.
• Experience supporting high-traffic or mission-critical applications.
• Experience building infrastructure or platform tooling used by large engineering organisations.
• Ownership of production reliability, on-call operations, incident response, or capacity planning.
• Experience working within sophisticated, large-scale distributed systems.
• Demonstrated improvements to SLOs/SLIs, observability, deployment reliability, infrastructure performance, or operational efficiency .
Why Join
• Solve challenging reliability, scalability, and performance problems across enterprise-grade production systems.
• Work extensively with technologies such as Kubernetes, AWS, Datadog, Terraform/Pulumi , and modern cloud-native tooling.
• Take meaningful ownership of production reliability, observability, infrastructure architecture, and operational improvements.
• Competitive hourly compensation reflecting your experience and technical expertise.
• Join a network of highly skilled engineers working on ambitious projects with leading technology and AI organisations.
Working with MercorPay, getting started and work, from Mercor's own pages
What the platform publishes in general. These are not extra terms confirmed for this particular role.
- Getting paid
- Hourly work is paid every Wednesday for the previous week, through Stripe Connect or Wise, whichever Mercor assigns to your region. Stripe holds the first payout for 7 days. talent.docs.mercor.com/how-to/payments, talent.docs.mercor.com/policies/contracts
- Before your first paid task
- An AI interview of about 20 minutes, reused for other roles that need it, then any assessments the role asks for. Before logging hours: ID verification through Persona, a tax form, the contract documents, the Insightful time tracker, and a background check the onboarding guide says usually takes one to two weeks. talent.docs.mercor.com/support/ai-interview, talent.docs.mercor.com/how-to/apply, talent.docs.mercor.com/policies/contracts, talent.docs.mercor.com/how-to/id-verification, talent.docs.mercor.com/working/project-onboarding
- How much work
- Hearing back after the AI interview usually takes 2 to 4 weeks. When a project ends you are not moved to a new one automatically. talent.docs.mercor.com/support/ai-interview, talent.docs.mercor.com/support/project
- Contract
- Independent contractor with Mercor.io Corporation of San Francisco, which deducts no taxes. talent.docs.mercor.com/policies/taxes-work-authorization, talent.docs.mercor.com/support/legal
Read on the pages linked above on 23 Sep 2026. Platforms change these terms, so check the linked page before you rely on one.
Alex's experience on MercorA personal account, not a promise about your project
Alexruns this site and has worked on Mercor himself. Written 31 Aug 2026.
- Every interview I took used an AI interviewer. They always checked my microphone and camera and asked me to share my screen, and some included a timed exercise of around 25 minutes.
- Many later applications needed no new interview from me. With the required assessments complete and no other outstanding steps, applying could be close to one click.
- The application I checked did not ask for a rate. My offer matched my minimum in Work Preferences. That does not establish that Mercor always caps higher offers at your preference.
- Onboarding and setup came to about 4 hours, with more security and tool setup. Of the three platforms I worked on, it was the most complicated for me. That is an estimate from my projects, not a platform average.
- Mercor required the Insightful tracker on my project. I observed app and website usage monitoring, and I am unsure which screenshot settings applied, so check the configuration.
- I was paid for hours logged, once every 14 days, and I have not experienced late or incorrect payments. That was my arrangement. Mercor's current documentation describes weekly payout cycles, so check your own offer.
One person's applications, not a promise about yours.
What happens after you apply, first-handHow does the pay compare?Across Coding & software eval roles, not this role alone
From our own daily reads of every open listing on the platforms we follow, not from Mercor's posting. How we count.
Pay across the field: Coding & software eval
Across 393 roles in this field with a stated hourly rate in US dollars, on 14 platforms, the middle half pays $65 to $120 an hour at the top of the range, and the median is $95. This role's top rate, $200, is in the top quarter. Of the 140 distinct rates we count, 133 are lower and 4 are higher.
| Platform | Roles | Top of range, per hour |
|---|---|---|
| Alignerr | 137 | $50 to $400 · median $100 |
| micro1 | 46 | $35 to $350 · median $110 |
| Handshake AI | 43 | $47 to $125 · median $80 |
| Meridial (Invisible) | 34 | $22 to $150 · median $60 |
| Mercor (this platform) | 32 | $60 to $150 · median $105 |
Sources and listing historyWhere this information comes from
This listing's history
- First seen here on 7 Oct 2026, and still on Mercor's list when we last read it on 13 Oct 2026.
- The listed pay has not changed since then.
- Posted by Mercor
- First seen by AIPayList
- Last seen live
- Listing ID
- list_AAABoRePE1qiY1-aJqFLRrSi
Pay as the source states it: “200 USD HOUR”.
Platforms sometimes change a rate after posting. Every listing here is re-read at least once a day and corrected when its source moves, so a difference you see on the platform is usually a change made since the last read. How freshness works.
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