Enterprise AI Evaluation Infrastructure Engineer

MaxIT Consulting - Max Corporate Group; San Francisco (CA); On-site; USD 140,000 - 200,000; Full time

Job summary

MaxIT Consulting - Max Corporate Group in San Francisco seeks an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems, and supporting infra for training and assessing 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 cross-functional teams on-site.

Qualifications

• Hands-on experience with AI environments, evaluations, or reinforcement learning infra.
• Proven ability to build and ship technical infrastructure.
• Understanding of evaluation methods, reward design, graders, and agent trajectories.
• Ability to work across languages and tech stacks as required.

Responsibilities

• Design evaluation environments for long-horizon enterprise agent workflows.
• Define tasks, state, tools, graders, and reward signals for evaluation.
• Build high-fidelity representations of complex enterprise software environments.
• Develop infrastructure for rollouts, orchestration, trajectory inspection, and grader pipelines.
• Measure correctness and efficiency across multi-step agent behavior.
• Investigate evaluation failures and reward-quality issues.
• Build production-quality systems, not notebook-only prototypes.

Skills

AI environments

RL infrastructure

Software engineering

Evaluation methodology

Cross-language work

Job description

MaxIT Consulting - Max Corporate Group in San Francisco seeks an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems, and supporting infra for training and assessing 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 cross-functional teams on-site.