AI Agent Evaluation Infra Engineer — SF On-Site

MaxIT Consulting - Max Corporate Group; San Francisco (CA); Presencial; USD 150.000 - 190.000; Jornada completa

Descripción de la vacante

MaxIT Consulting - Max Corporate Group in San Francisco is seeking an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems, and the supporting infrastructure used to train and assess long-horizon enterprise AI agents.

You will tackle engineering and research problems behind realistic agent environments, post-training systems, and reliable evaluation of complex multi-step workflows, collaborating with a team on production-grade infrastructure.

Formación

• Experience with AI environments, evaluations, RL infrastructure, or related agent-training systems.
• Strong software engineering fundamentals.
• Ability to build and ship technical infrastructure.
• Understanding of evaluation methodology, reward design, graders, and agent trajectories.
• Ability to work across languages and technology stacks.

Responsabilidades

• Design evaluation environments for long-horizon enterprise agent workflows.
• Define tasks, state, tools, graders, and reward signals used to evaluate and improve agents.
• Build high-fidelity representations of complex enterprise software environments.
• Develop infrastructure for rollouts, orchestration, trajectory inspection, and grader pipelines.
• Measure both correctness and efficiency across multi-step agent behavior.
• Investigate evaluation failures, reward-quality issues, and agent behavior.
• Build production-quality systems rather than notebook-only research prototypes.

Conocimientos

AI environments

Evaluations

Reinforcement learning

Software engineering

Production infrastructure

Cross-language work

Descripción del empleo

MaxIT Consulting - Max Corporate Group in San Francisco is seeking an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems, and the supporting infrastructure used to train and assess long-horizon enterprise AI agents.

You will tackle engineering and research problems behind realistic agent environments, post-training systems, and reliable evaluation of complex multi-step workflows, collaborating with a team on production-grade infrastructure.