AI Summary
Design, build, and optimize infrastructure for AI agents. Develop backend services and APIs. Collaborate with research and product teams.
Key Highlights
Design and optimize infrastructure for AI agents
Develop backend services and APIs
Collaborate with research and product teams
Implement monitoring and observability mechanisms
Evaluate and refine infrastructure performance
Technical Skills Required
Benefits & Perks
Competitive hourly rate ($74-$168/hour)
Flexible work arrangement (20-30 hours/week)
Job Description
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: AI Agent Infrastructure Engineer
Type: Contract
Compensation: $74–$168/hour
Commitment: 20–30 hours/week
Role Responsibilities
- Design, build, and optimize infrastructure for training, deploying, and scaling AI agents across distributed systems.
- Develop robust backend services, APIs, and orchestration frameworks that support multi-agent workflows and high-performance compute environments.
- Collaborate closely with research and product teams to integrate model-serving pipelines, memory systems, and reasoning components.
- Implement monitoring, observability, and failover mechanisms to ensure high system reliability and fault tolerance.
- Evaluate and refine infrastructure performance, identifying bottlenecks and improving efficiency across data, compute, and model layers.
- Participate in synchronous collaboration sessions to review architecture decisions, troubleshoot distributed systems, and iterate on design improvements.
Must-Have
- Strong background in Computer Science, Software Engineering, or Systems Design.
- Experience with cloud computing (AWS, GCP, or Azure) and Docker and Kubernetes.
- Proficiency in Go, Rust, Python, or C++.
- Excellent collaboration and communication skills.
- Ability to commit 20–30 hours per week.
- Familiarity with LLM inference pipelines, multi-agent architectures, or reinforcement learning environments.
- Knowledge of network optimization, data streaming, and caching architectures.
- Upload resume
- AI interview based on your resume
- Submit form
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
- For any help or support, reach out to: support@mercor.com
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