Cloud Engineer - AI

About the Company

AfterQuery is an expert data and research lab that develops evaluation and training data to help leading AI labs measure and improve their models’ performance on real-world professional tasks. The company focuses on exploring the capabilities and limitations of artificial intelligence through specialized datasets and experimentation. AfterQuery is backed by investors including Y Combinator and Box Group.

About the Role

AfterQuery is seeking experienced Cloud Engineers for independent contract work developing and evaluating cloud infrastructure scenarios used to test AI models. In this role, you will create realistic technical challenges, develop reference solutions, and assess model-generated outputs for accuracy, security, and cost efficiency.

The work focuses on practical cloud engineering knowledge, from architecture design to incident response. Contributors use their professional experience to identify solutions that may appear reasonable but would fail, introduce security risks, or create unnecessary costs in production environments.

Key Responsibilities

• Develop realistic cloud infrastructure scenarios covering architecture design, automation, and incident response.
• Write reference answers that explain the architectural reasoning behind technical decisions.
• Evaluate AI-generated outputs for technical correctness, security, and cost efficiency.
• Identify configurations that appear plausible but would fail in production or lead to unnecessary spending.
• Apply practical cloud engineering experience to assess infrastructure designs and automation approaches.
• Document architectural decisions and operational reasoning clearly.

Required Qualifications

• At least two years of professional cloud engineering experience with AWS, Azure, or Google Cloud Platform (GCP).
• Hands-on experience with infrastructure as code tools such as Terraform, CloudFormation, or similar technologies.
• Strong practical knowledge in at least one area of cloud engineering, such as networking, containers, serverless architecture, or cost optimization.
• Clear written English and the ability to explain technical and architectural decisions.
• Ability to commit at least 10 hours per week.

Preferred Qualifications

• Certifications such as AWS Solutions Architect, Azure Administrator, or GCP Professional.
• Experience with Kubernetes and container orchestration.
• Experience with multi-cloud environments or large-scale cloud migrations.

Contract Terms and Compensation

• Hourly compensation ranges from $85 to $165, based on experience.
• Payments are issued weekly through Stripe.
• The rate is determined by experience and is not negotiated downward after work begins.
• Independent contractor engagement with ongoing project work rather than isolated task batches.
• Minimum commitment of 10 hours per week, with no maximum specified.
• Contributors can adjust their weekly hours according to their availability.
• Fully remote and asynchronous work with no fixed working hours.

Application and Hiring Process

• Resume Review: Applications are reviewed against a published rubric, and each applicant receives a decision.
• Written Assessment: Applicants may be asked to complete a written assessment for further placement.
• Onboarding: Selected contractors sign the contractor agreement, connect their Stripe account, and receive platform access.
• Project Matching: Contractors are matched with active projects in their area of expertise, usually within one week of onboarding.

Work Arrangement

This is a fully remote, asynchronous independent contractor opportunity. Contributors work on ongoing projects and can adjust their weekly hours while maintaining the minimum commitment of 10 hours per week.

Why Join AfterQuery

• Contribute professional cloud engineering expertise to the development and evaluation of advanced AI models.
• Work remotely with a flexible schedule and no fixed hours.
• Receive weekly payments at professional hourly rates.
• Apply your specialization to ongoing projects aligned with your experience.
• Help assess how AI models handle real-world cloud infrastructure and automation challenges.