LLM Systems Engineer - Fully Remote | Upto $500/task Task based
Budget / Salary$100–500
TypeFull-time job
LocationCanada
Posted1 hour ago
About the job
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.
Position: Agent Engineer
Type:Contract
Compensation:$100–$500/hour
Location:Remote
Role Responsibilities
Build and operate LLM agents in production environments.
Evaluate agent performance and determine improvements after changes.
Manage long-running agents, including scheduled jobs and cloud sandboxes.
Analyze adoption patterns of internal assistants within organizations.
Focus on internal monoagents, shared memory, and reusable skills.
Ensure visibility into agent actions and associated costs.
Qualifications
Must-Have
Experience shipping agents used by real users.
Ability to assess agent performance improvements.
Knowledge of long-running work and cloud sandboxes.
Insight into internal assistant adoption within organizations.
Interview Process
Initial short conversational AI interview; no coding or take-home tasks.
Live 30-minute conversation with our team.
Compensation of $100 to $500 for the conversation, based on experience.
Application Process (Takes 20–30 mins to complete)
Upload resume
AI interview based on your resume
Submit form
Resources & Support
For details about the interview process and platform information, please check:
For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
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.
Position: Agent Engineer
Type:Contract
Compensation:$100–$500/hour
Location:Remote
Role Responsibilities
Build and operate LLM agents in production environments.
Evaluate agent performance and determine improvements after changes.
Manage long-running agents, including scheduled jobs and cloud sandboxes.
Analyze adoption patterns of internal assistants within organizations.
Focus on internal monoagents, shared memory, and reusable skills.
Ensure visibility into agent actions and associated costs.
Qualifications
Must-Have
Experience shipping agents used by real users.
Ability to assess agent performance improvements.
Knowledge of long-running work and cloud sandboxes.
Insight into internal assistant adoption within organizations.
Interview Process
Initial short conversational AI interview; no coding or take-home tasks.
Live 30-minute conversation with our team.
Compensation of $100 to $500 for the conversation, based on experience.
Application Process (Takes 20–30 mins to complete)
Upload resume
AI interview based on your resume
Submit form
Resources & Support
For details about the interview process and platform information, please check:
For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
Originally posted on Himalayas
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Job sourced from Himalayas. Applications happen directly on the original platform — we never collect your data.