Senior Backend Engineer – Cloud, Ai & Microservices

Cox Automotive UK Limited; Lisboa; A distancia; EUR 63.000 - 105.000; Jornada completa

Descripción de la vacante

You will review model-generated solutions, compare outputs across models, and apply engineering judgment to real-world infra scenarios. A strong background in DevOps, SRE, and cloud platforms is essential, with a remote-capable setup.

Formación

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.

Responsabilidades

• Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
• Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.
• Identify bugs, edge cases, reliability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models to assess strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.

Conocimientos

DevOps

SRE

Cloud Engineering

Herramientas

AWS

Azure

GCP

Kubernetes

Terraform

CI/CD pipelines

Observability

Descripción del empleo

Cloud Engineer - Fully Remote | Upto $85/hr

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Role Responsibilities

• Use frontier AI coding agents to complete and evaluate complex infrastructure engineering tasks.
• Review model-generated implementations involving cloud platforms, Kubernetes, CI/CD systems, observability, and infrastructure automation.
• Identify bugs, edge cases, reliability issues, and failure modes in model outputs.
• Compare outputs from multiple frontier models to assess their strengths and weaknesses.
• Apply professional engineering judgment to realistic infrastructure engineering scenarios.

Qualifications

Must-Have

• 2+ years of professional DevOps, SRE, or Cloud Engineering experience.
• Experience with AWS, Azure, GCP, Kubernetes, Terraform, CI/CD pipelines, or observability tooling.
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools.
• Ability to evaluate model-generated infrastructure and reliability engineering solutions.

Preferred

• Experience supporting production-scale systems.
• $400 per accepted task
• Compensation tied to accepted work.