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.
In-depth analysis: how it works, pay rates, pros & cons, and tips to get hired.
