Mercor
Mercor is hiring
AI Agent Infrastructure Engineers
on behalf of a leading
AI Lab
developing scalable systems to power the next generation of intelligent, autonomous agents. This is a unique opportunity to work with world-class AI researchers and engineers, building the infrastructure that enables advanced reasoning, multi-agent coordination, and real-world deployment of AI systems. 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
(4-hour windows, 2–3 times per week) to review architecture decisions, troubleshoot distributed systems, and iterate on design improvements.
Requirements Strong background in
Computer Science, Software Engineering, or Systems Design , with focus on large-scale distributed infrastructure.
Experience with
cloud computing (AWS, GCP, or Azure)
and containerization/orchestration tools such as
Docker and Kubernetes .
Proficiency in backend programming languages such as
Go, Rust, Python, or C++ .
Familiarity with
LLM inference pipelines ,
multi-agent architectures , or
reinforcement learning environments
is a strong plus.
Knowledge of
network optimization, data streaming, and caching architectures
preferred.
Excellent collaboration and communication skills.
Ability to commit
20–30 hours per week , including required synchronous collaboration sessions.
Why Join Work directly with a
world-class AI research lab
building the infrastructure behind tomorrow’s intelligent agent ecosystems.
Influence the foundations of
AI scalability, reliability, and deployment , enabling complex agents to operate in real-world environments.
Enjoy
schedule flexibility
— select your own 4-hour collaboration windows and manage your 20–30 hour work week.
Be engaged as an
hourly contractor through Mercor , giving you autonomy while contributing to mission-critical AI infrastructure projects.
Collaborate with
top systems engineers, researchers, and AI developers
working at the intersection of distributed systems and advanced intelligence.
Join a
global network of technical experts
shaping how the next generation of AI agents reason, interact, and evolve at scale.
#J-18808-Ljbffr
AI Agent Infrastructure Engineers
on behalf of a leading
AI Lab
developing scalable systems to power the next generation of intelligent, autonomous agents. This is a unique opportunity to work with world-class AI researchers and engineers, building the infrastructure that enables advanced reasoning, multi-agent coordination, and real-world deployment of AI systems. 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
(4-hour windows, 2–3 times per week) to review architecture decisions, troubleshoot distributed systems, and iterate on design improvements.
Requirements Strong background in
Computer Science, Software Engineering, or Systems Design , with focus on large-scale distributed infrastructure.
Experience with
cloud computing (AWS, GCP, or Azure)
and containerization/orchestration tools such as
Docker and Kubernetes .
Proficiency in backend programming languages such as
Go, Rust, Python, or C++ .
Familiarity with
LLM inference pipelines ,
multi-agent architectures , or
reinforcement learning environments
is a strong plus.
Knowledge of
network optimization, data streaming, and caching architectures
preferred.
Excellent collaboration and communication skills.
Ability to commit
20–30 hours per week , including required synchronous collaboration sessions.
Why Join Work directly with a
world-class AI research lab
building the infrastructure behind tomorrow’s intelligent agent ecosystems.
Influence the foundations of
AI scalability, reliability, and deployment , enabling complex agents to operate in real-world environments.
Enjoy
schedule flexibility
— select your own 4-hour collaboration windows and manage your 20–30 hour work week.
Be engaged as an
hourly contractor through Mercor , giving you autonomy while contributing to mission-critical AI infrastructure projects.
Collaborate with
top systems engineers, researchers, and AI developers
working at the intersection of distributed systems and advanced intelligence.
Join a
global network of technical experts
shaping how the next generation of AI agents reason, interact, and evolve at scale.
#J-18808-Ljbffr