Enterprise AI Evaluation Infra Engineer — SF On-Site

MaxIT Consulting - Max Corporate Group; San Francisco (CA); On-site; USD 160,000 - 230,000; Full time

Job summary

MaxIT Consulting - Max Corporate Group in San Francisco, CA seeks an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems and supporting infrastructure for training and assessing long-horizon enterprise AI agents. The role anchors on-site with emphasis on real-world production quality rather than notebook-style research.

You will design evaluation environments, define tasks, state, tools, graders and reward signals, and develop scalable pipelines for rollouts and

Qualifications

• Hands-on experience with AI environments, evaluations, reinforcement learning infrastructure, or related agent-training systems.
• Strong software engineering fundamentals.
• Demonstrated 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 based on system requirements.

Responsibilities

• 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.

Skills

AI environments

RL infra

Software engineering

Evaluation methods

Cross-language

Tools

Grader pipelines

Evaluation tooling

Job description

MaxIT Consulting - Max Corporate Group in San Francisco, CA seeks an Agent Evaluation Infrastructure Engineer to build environments, evaluation systems and supporting infrastructure for training and assessing long-horizon enterprise AI agents. The role anchors on-site with emphasis on real-world production quality rather than notebook-style research.

You will design evaluation environments, define tasks, state, tools, graders and reward signals, and develop scalable pipelines for rollouts and