Remote Software Engineer - AI Trainer ($100-$160 per hour)

Mercor is hiring

• Software Engineers
• on behalf of a leading AI Lab building scalable systems to power the next generation of
• intelligent, autonomous agents
• . This role sits at the intersection of
• distributed systems engineering and agentic AI
• , focused on enabling advanced reasoning, multi-agent coordination, and real-world deployment at scale.
• ## Responsibilities - Design, build, and optimise
• distributed infrastructure
• for training, deploying, and scaling AI agents across high-performance compute environments. - Develop
• core backend systems
• (services, APIs, and orchestration layers) that support agent lifecycles, tool execution, memory access, and multi-agent coordination. - Collaborate closely with
• research and applied AI teams
• to integrate model-serving pipelines, agent reasoning loops, memory stores, and planning components into production systems. - Build and maintain
• agent runtime infrastructure
• , including task scheduling, state management, inter-agent communication, and execution reliability. - Implement
• monitoring, observability, and fault-tolerance
• mechanisms for long-running agent processes and distributed workflows. - Evaluate and improve system performance across
• compute, networking, storage, and inference layers
• , identifying and resolving bottlenecks. - Participate in synchronous collaboration sessions (4-hour windows, 2–3 times per week) to review architecture decisions, troubleshoot distributed systems, and iterate on design improvements.
• ## Requirements - Strong foundation in
• Computer Science, Software Engineering, or Systems Design
• , with experience building large-scale distributed systems. - Proficiency in one or more backend or systems programming languages such as
• Go, Rust, Python, C++, Java, Scala, C#, Kotlin, or TypeScript / JavaScript
• . - Experience with
• cloud infrastructure
• (AWS, GCP, or Azure) and
• containerisation / orchestration
• tools such as Docker and Kubernetes. - Strong experience designing
• production-grade backend services
• , APIs, and distributed systems. - Familiarity with
• LLM inference pipelines, agent frameworks, multi-agent architectures, or reinforcement learning environments
• is a strong plus. - Knowledge of
• networking, data streaming, caching, and performance optimisation
• in distributed systems. - Excellent collaboration and communication skills. - Ability to commit
• 30-40 hours per week
• , including required synchronous collaboration sessions.
• ## Why Join - Work directly with a
• world-class AI research lab
• building the infrastructure behind next-generation agentic systems. - Influence how
• intelligent agents are trained, deployed, and operated at scale
• in real-world environments. - Operate at the frontier of
• software engineering and autonomous AI
• , contributing to foundational system design. - Collaborate with leading systems engineers, AI researchers, and agent developers tackling hard problems in scalability, reliability, and autonomy. - Join a global network of experts shaping the future of
• agent-driven AI infrastructure