LLM Engineer (Remote)
Hire Feed · France
- Hybrid
- Part-time
- $50,000 / year
- France
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Job highlights
- Design and evaluate autonomous AI agents.
- Provide feedback to leading AI organizations.
- Train Large Language Models for workflows.
- Assess production-grade software architecture.
- Requires backend engineering and coding experience.
About the role
LLM Engineer (Remote)
Location: Remote (Finland, France, Italy, Norway)
Work Mode: Fully Remote
Role Overview
Help design and evaluate autonomous AI agents across multiple LLMs, spanning health, education, daily life, and other real-world domains (all coding work). Shape the future of agentic AI systems by providing expert human feedback to leading AI organisations. Help train Large Language Models (LLMs) for complex, multi-step architectural workflows.
Key Responsibilities
AI Agent Evaluation
- Write evaluation rubrics with objective pass/fail criteria
- Debug agent traces to identify failure patterns
- Stress test agents against edge cases, prompt injection, and tool misuse
Technical Assessment
- Assess production-grade modular software architecture
- Analyse multi-turn system interactions and behaviours
- Provide high-density technical feedback for LLM training
Project Workflow
- Create an account and upload a resume/ID
- Complete the onboarding assessment
- Start earning through flexible task assignments
Qualifications
- Experience in backend engineering, AI automation, or complex systems integration
- Proven ability to build and maintain production-grade software with modular separation (e.g., distinct services for data parsing, logic processing, and reporting)
- Strong command of at least two major languages (e.g., Python, JavaScript, Go, or Java) and experience working with SQL databases
- Practical experience building for live, non-mocked environments and handling multi-turn system interactions
Preferred (Nice to Have)
- Experience integrating agents with live tools such as Supabase, Gmail, and other APIs
- Familiarity with persistent state and session-tracking patterns
- Experience identifying privacy leaks, authority escalation, or indirect prompt injection vulnerabilities
Compensation
Hourly compensation ranges from USD $30–$50, depending on experience and task complexity. Payments are issued weekly via supported payout platforms (e.g., PayPal or AirTM). Full compensation details are provided prior to task acceptance.
Equal Opportunity Statement
Selection decisions are based solely on skills, qualifications, and project requirements. We are committed to inclusive and fair engagement practices and consider all qualified applicants without regard to legally protected characteristics.
Key skills/competency
- LLM Engineer
- AI Agents
- Backend Engineering
- Software Architecture
- Python
- JavaScript
- SQL Databases
- System Interactions
- Prompt Engineering
- AI Automation
Skills & topics
- LLM Engineer
- AI Agent
- Backend Engineering
- Software Architecture
- Python
- JavaScript
- SQL
- AI Automation
- Prompt Engineering
- Remote
How to get hired
- Tailor your resume: Highlight backend engineering, AI automation, and complex systems integration experience. Quantify achievements in production environments.
- Showcase technical skills: Emphasize proficiency in Python, JavaScript, Go, or Java, and SQL database experience. Detail experience with modular software architecture.
- Address preferred qualifications: Mention any experience with API integrations, persistent state, or security vulnerabilities if applicable.
- Prepare for onboarding: Be ready to complete an assessment and provide necessary identification after account creation.
- Understand compensation: Review the hourly rate range ($30-$50) and payment methods before accepting tasks.
Technical preparation
Practice building modular software with distinct services.,Code in Python, JavaScript, Go, or Java.,Work with SQL databases and live environments.,Familiarize yourself with AI agent evaluation criteria.
Behavioral questions
Describe a complex system you engineered.,How do you debug agent failure patterns?,How do you provide constructive technical feedback?,How do you handle stress testing and edge cases?
Frequently asked questions
- What are the primary responsibilities of an LLM Engineer at Hire Feed?
- As an LLM Engineer at Hire Feed, you will be responsible for designing and evaluating autonomous AI agents, providing technical feedback to train Large Language Models, and assessing production-grade software architecture. This involves debugging agent traces, stress-testing agents, and analyzing multi-turn system interactions.
- What programming languages are required for the LLM Engineer role at Hire Feed?
- The LLM Engineer role at Hire Feed requires a strong command of at least two major programming languages, such as Python, JavaScript, Go, or Java. Experience with SQL databases is also a key requirement for this position.
- Is the LLM Engineer position at Hire Feed remote?
- Yes, the LLM Engineer position at Hire Feed is fully remote. The company specifies that candidates can be located in Finland, France, Italy, or Norway.
- What is the compensation for an LLM Engineer at Hire Feed?
- The hourly compensation for an LLM Engineer at Hire Feed ranges from USD $30 to $50, depending on experience and task complexity. Payments are issued weekly.
- What kind of experience is needed to be considered for the LLM Engineer role?
- To be considered for the LLM Engineer role, you need experience in backend engineering, AI automation, or complex systems integration. You should also have proven ability to build and maintain production-grade software with modular separation and practical experience in live, non-mocked environments.
- How does Hire Feed handle payments for LLM Engineers?
- Hire Feed issues payments weekly for LLM Engineers through supported payout platforms such as PayPal or AirTM. Full compensation details are provided before task acceptance.
- What is the purpose of the onboarding assessment for the LLM Engineer role?
- The onboarding assessment for the LLM Engineer role at Hire Feed is designed to evaluate your skills and qualifications relevant to the project requirements, ensuring a good match for the tasks available.