About The JobMercor 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: Software Engineer
Type: Contract
Compensation: $100–$160/hour
Commitment: 30–40 hours/week
Role Responsibilities- Design, build, and optimize distributed infrastructure for training, deploying, and scaling AI agents across high-performance compute environments.
- Develop core backend systems including services, APIs, and orchestration layers to support agent lifecycles, tool execution, memory access, and multi-agent coordination.
- Collaborate 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.
QualificationsMust-Have- 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 containerization/orchestration tools such as Docker and Kubernetes.
- Strong experience designing production-grade backend services, APIs, and distributed systems.
- Knowledge of networking, data streaming, caching, and performance optimization in distributed systems.
- Excellent collaboration and communication skills.
- Ability to commit 30-40 hours per week, including required synchronous collaboration sessions.
Preferred- Familiarity with LLM inference pipelines, agent frameworks, multi-agent architectures, or reinforcement learning environments.
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
- 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.