Cloud Computing Expert

Role Overview

Mercor is partnering with leading AI labs on Project Atlas — an initiative to build realistic enterprise environments that frontier AI agents are trained and evaluated in. We're seeking experienced cloud-computing professionals from major hyperscalers and Fortune 500 enterprises running large cloud deployments (e.g., AWS, Microsoft Azure, Google Cloud, Oracle Cloud, Snowflake, Databricks, and Fortune 500 platform / infrastructure teams) to recreate the digital workspaces they run every day and design the tasks that genuinely challenge state-of-the-art AI.

You'll bring your expertise in cloud architecture, site reliability, platform engineering, DevOps / DevSecOps, or cloud FinOps to build a high-fidelity environment that mirrors the tools, files, and cross-functional workflows of a modern cloud organization — and then author tasks grounded in the programs you actually run today.

Key Responsibilities

• Build a realistic digital workspace centered on the Drive folders you use day-to-day — the architecture docs, runbooks, RFCs, incident post-mortems, capacity plans, cost reports, SRE review decks, and email threads that reflect how you actually organize your work — with some representation of the platforms that support it (e.g., HashiCorp Terraform, Datadog / Splunk, GitHub Actions, Okta)

• Design multi-step tasks grounded in your real workflows that require navigating multiple apps, files, and stakeholders in a way that meaningfully challenges frontier AI agents

• Collaborate with other cloud-computing experts in your field to design the environment, shape task scope, and review each other's scenarios for realism and rigor

• Work asynchronously with research teams to refine task designs and evaluation criteria for cloud-computing agent benchmarks

• Contribute to frontier AI research and benchmarking — the work you produce directly informs how leading labs train and evaluate the next generation of AI systems

Ideal Qualifications

• 3+ years of full-time experience at a major hyperscaler (AWS, Azure, GCP, Oracle Cloud), a cloud-data platform (Snowflake, Databricks), or a Fortune 500 platform / infrastructure team

• Background in one or more areas such as:

  • Cloud architecture / solutions engineering (multi-account, multi-region, hybrid)

  • Site reliability engineering or production engineering

  • Platform / developer-experience engineering (IaC, internal developer platforms)

  • DevOps / DevSecOps, CI/CD, or container / Kubernetes operations

  • Cloud security, compliance (SOC 2, ISO 27001, FedRAMP), or cloud FinOps

• Certifications a plus: AWS Solutions Architect / SysOps / DevOps, Azure Solutions Architect, GCP Professional Cloud Architect, CKA / CKAD

• Day-to-day use of HashiCorp Terraform / Pulumi, Splunk / Datadog, GitHub Actions / CircleCI, and Okta / Microsoft Entra ID

• Strong analytical thinking and writing — able to translate cloud-ops workflows into structured task specs

Compensation Note

• Task Completion Pay: Competitive and based on task quality (~$1,750 – $2,150 per completed task, subject to change as the project evolves)

• Performance Bonus: Top performers receive a weekly bonus incentive on top of their per task rate!

• Hourly Opportunity: Top performers may be invited to transition to an hourly compensation model based on sustained quality and throughput.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract and Payment Terms

• You will be engaged as an independent contractor.
• This is a fully remote role that can be completed on your own schedule.
• Projects can be extended, shortened, or concluded early depending on needs and performance.
• Your work at Mercor will not involve access to confidential or proprietary information from any employer, client, or institution.
• Payments are weekly on Stripe or Wise based on services rendered.
• Please note: We are unable to support H1-B or STEM OPT candidates at this time.

About Mercor

Mercor partners with leading AI labs and enterprises to train frontier models using human expertise. You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.