Remote | Software Engineer — $100–$160/hour

Role overview

Part-time independent contractor opportunity for experienced software engineers to help build scalable infrastructure for agentic AI. You will work at the intersection of distributed systems engineering and agentic AI, supporting the training, deployment, and scaling of multi-agent systems.

Responsibilities

• Distributed Systems & Infrastructure Engineering
  • Design, build, and optimize distributed infrastructure for training, deploying, and scaling AI agents.
  • Evaluate and improve performance across compute, networking, storage, and inference layers; identify and resolve bottlenecks.
  • Implement monitoring, observability, and fault tolerance for long-running agent processes and workflows.
• Backend Systems & Agent Runtime Development
  • Develop core backend systems: services, APIs, and orchestration layers supporting agent lifecycles, tool execution, memory access, and multi-agent coordination.
  • Build agent runtime infrastructure: task scheduling, state management, inter-agent communication, and reliable execution.
  • Support production-grade infrastructure for complex agent workflows and autonomous behavior.
• AI Systems Collaboration & Technical Iteration
  • Collaborate with research and applied AI teams to integrate model-serving pipelines, reasoning loops, memory stores, and planning into production.
  • Participate in architecture reviews, troubleshooting, and iterative design improvement.

Requirements

• Strong foundation in Computer Science / Software Engineering / Systems Design with experience building large-scale distributed systems.
• Proficiency in one or more backend/systems languages such as Go, Rust, Python, C++, Java, Scala, C#, Kotlin, or TypeScript/JavaScript.
• Experience with cloud infrastructure: AWS, GCP, or Azure.
• Experience with containerization and orchestration: Docker and Kubernetes.
• Strong skills in designing production-grade backend services, APIs, and distributed systems.
• Excellent collaboration and communication.

Preferred qualifications

• Familiarity with LLM inference pipelines, agent frameworks, multi-agent architectures, or reinforcement learning environments.
• Comfort with networking, data streaming, caching, and performance optimization in distributed systems.
• Ability to work across systems engineering and applied AI infrastructure.

Contract details

• Independent contractor (consulting), fully remote with flexible scheduling.