[Hiring] AI Agent Evaluation Engineer @Cresta

Role Description

Cresta’s AI Receptionist answers the phone for small businesses that would otherwise miss the call. It handles millions of conversations a month today, making sure no call goes unanswered and helping owners complete the front-office tasks that keep their business running, and it does so across hundreds of customers. Whether those conversations are actually good is the single most important question in the business, and it deserves a full-time owner. That’s you.

As our first AI Agent Evaluation Engineer, you define what quality means for every agent we run, you build the systems that measure it across every conversation, and you are the person the company trusts when the question is “how good is it, really?”

The work combines hands-on conversation analysis, rigorous evaluation design, and engineering execution:

• Reading and annotating real conversations to learn how the agent actually fails.
• Building the automated evaluation systems (LLM-based judges, golden sets, regression suites) that measure those failures at scale.
• Keeping those systems honest by calibrating them against human judgment.
• Fixing what you find is welcome but not the core of the job; an accurate, prioritized picture of agent quality is.

Qualifications

• 3+ years of professional experience in software engineering, applied ML, or data-intensive research roles, including at least 1–2 years working hands-on with LLM-based systems in production.
• Bachelor’s or Master’s degree in Computer Science, Computational Linguistics, Cognitive Science, Statistics, or a related field, or equivalent practical experience.
• Built and operated an end-to-end evaluation system for a production LLM product (agent or otherwise): rubric, human labels, automated judge, regression suite.
• Deep understanding of evaluation methodology: what golden sets, judges, regression suites, and calibration are for, and when each fails.
• Fluent in how LLM agents work: prompts, tool calls, context handling, multi-turn state.
• Strong programming skills in Python and experience with LLM APIs; able to build and ship evaluation tooling independently.
• Able to write a rubric that independent reviewers would score the same way, and to measure whether they do.
• Able to design a test from an open-ended quality question.
• Willing to do non-scalable work weekly, both yourself and by directing our QA partners.
• Professional fluency in at least one language other than English, sufficient to evaluate multilingual agent behavior directly.
• Strong written communication; you author the guidelines others follow.

Requirements

• Define and maintain the evaluation rubric for the agent across three axes: adherence, outcome, and conversation experience.
• Write the annotation guidelines and failure taxonomy the team uses to talk about failures precisely.
• Classify and prioritize failure modes by severity and frequency.
• Review production conversations by hand every week; open-code failures and cluster them.
• Trace each failure to its likely cause and route it to the right owner with enough evidence to act on.
• Evaluate across languages and report quality by segment.
• Build and operate the evaluation pipeline that scores every production conversation.
• Calibrate every automated judge against human labels before trusting it.
• Design sampling strategies so that reported changes in quality are real.
• Maintain the failure-mode coverage map.
• Design evaluations for behaviors no standard harness covers.
• Define the quality and latency thresholds the agent is held to.
• Report quality trends to internal stakeholders and customers clearly.
• Partner with forward-deployed engineers, backend engineers, product managers, and the voice/language engineering team.
• Document methodology so results are reproducible.

Benefits

• Comprehensive medical, dental, and vision coverage with plans to fit you and your family.
• Flexible PTO to take the time you need, when you need it.
• Paid parental leave for all new parents welcoming a new child.
• Retirement savings plan to help you plan for the future.
• Remote work setup budget to help you create a productive home office.
• Monthly wellness and communication stipend to keep you connected and balanced.
• In-office meal program and commuter benefits provided for onsite employees.