

Great Value Hiring
SWE (Terminal and CLI Dev Tools Focused)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a SWE (Terminal and CLI Dev Tools Focused) with a contract length of 1-2 weeks, offering $75-$80/hr. Key skills include 3+ years in software engineering, strong bash scripting, Docker experience, and infrastructure debugging expertise.
🌎 - Country
United Kingdom
💱 - Currency
$ USD
-
💰 - Day rate
640
-
🗓️ - Date
April 11, 2026
🕒 - Duration
1 to 3 months
-
🏝️ - Location
Unknown
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
United Kingdom
-
🧠 - Skills detailed
#MySQL #Bash #CLI (Command-Line Interface) #Replication #AI (Artificial Intelligence) #Containers #Debugging #Docker #PostgreSQL #Version Control #Security #Shell Scripting #Scripting #Databases #GIT #Redis
Role description
SWE (Terminal and CLI Dev Tools Focused) [$75-$80/hr]
Experienced Software Engineers to evaluate and compare the performance of AI-powered CLI coding agents on real-world infrastructure debugging tasks
You will solve TerminalBench tasks: real-world broken infrastructure scenarios running inside Docker containers. You'll use AI CLI agents to help you. Each task presents a failing system (databases, networking, security, pipelines) that you must diagnose and fix by writing a bash script, guided by AI agents in turn.
Role Responsibilities
• Solve the same infrastructure debugging task with CLI-based AI coding agent
• Diagnose broken systems inside Docker containers (databases, TLS, pipelines, replication, access control)
• Write bash scripts that fix the root cause and survive service restarts
• Compare agents' approaches and rank their performance after each task
Good Candidature
• 3+ years of experience in software engineering, with hands-on debugging of systems and infrastructure
• Strong bash/shell scripting proficiency: you'll be writing non-trivial fix scripts from scratch
• Docker and containerization experience: every task runs inside a Docker container you'll need to explore via docker exec
• Infrastructure and systems debugging skills: experience with PostgreSQL, MySQL, Redis, nginx, TLS, systemd, log analysis, or similar
• Familiarity with version control workflows (Git, PRs, issue tracking)
• Experience with AI coding tools (Copilot, Cursor, Claude, or similar) is a plus: you need to effectively prompt and evaluate AI output, not just code yourself
Project Timeline
• Start Date: Immediate
• Duration: 1-2 weeks
• Commitment: Part-time (15-25 hours/week, with flexibility up to 40 hours/week)
SWE (Terminal and CLI Dev Tools Focused) [$75-$80/hr]
Experienced Software Engineers to evaluate and compare the performance of AI-powered CLI coding agents on real-world infrastructure debugging tasks
You will solve TerminalBench tasks: real-world broken infrastructure scenarios running inside Docker containers. You'll use AI CLI agents to help you. Each task presents a failing system (databases, networking, security, pipelines) that you must diagnose and fix by writing a bash script, guided by AI agents in turn.
Role Responsibilities
• Solve the same infrastructure debugging task with CLI-based AI coding agent
• Diagnose broken systems inside Docker containers (databases, TLS, pipelines, replication, access control)
• Write bash scripts that fix the root cause and survive service restarts
• Compare agents' approaches and rank their performance after each task
Good Candidature
• 3+ years of experience in software engineering, with hands-on debugging of systems and infrastructure
• Strong bash/shell scripting proficiency: you'll be writing non-trivial fix scripts from scratch
• Docker and containerization experience: every task runs inside a Docker container you'll need to explore via docker exec
• Infrastructure and systems debugging skills: experience with PostgreSQL, MySQL, Redis, nginx, TLS, systemd, log analysis, or similar
• Familiarity with version control workflows (Git, PRs, issue tracking)
• Experience with AI coding tools (Copilot, Cursor, Claude, or similar) is a plus: you need to effectively prompt and evaluate AI output, not just code yourself
Project Timeline
• Start Date: Immediate
• Duration: 1-2 weeks
• Commitment: Part-time (15-25 hours/week, with flexibility up to 40 hours/week)






