AI Agent Infrastructure Engineer (Contract)

Mercor • Germany
Remote
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AI Summary

Design, build, and optimize infrastructure for AI agents. Develop backend services and APIs. Collaborate with research and product teams.

Key Highlights
Design, build, and optimize infrastructure for training, deploying, and scaling AI agents
Develop robust backend services, APIs, and orchestration frameworks
Collaborate with research and product teams to integrate model-serving pipelines
Implement monitoring, observability, and failover mechanisms
Evaluate and refine infrastructure performance
Technical Skills Required
Cloud computing (AWS, GCP, Azure) Docker Kubernetes Go Rust Python C++
Benefits & Perks
Hourly compensation: $74–$168/hour
Flexible work hours (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.

Qualifications

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.

Preferred

  • Familiarity with LLM inference pipelines, multi-agent architectures, or reinforcement learning environments.
  • Knowledge of network optimization, data streaming, and caching architectures.

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: https://talent.docs.mercor.com/welcome/welcome
  • For any help or support, reach out to: support@mercor.com

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

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