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2 дня назад

AI Engineer

300 000 - 350 000$
Формат работы
onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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TL;DR
AI Engineer (Agent Evaluation/Insurance AI): Building evaluation frameworks, datasets, benchmarking systems, and continuous improvement pipelines for AI agents handling complex insurance workflows with an accent on multi-step trajectories, tool use, grading systems, and model performance tradeoffs. Focus on designing production-grade evaluation infrastructure, detecting quality regressions, and turning agent failures and customer feedback into measurable improvements.

Location: San Francisco, United States; on-site five days per week

Salary: $300K–$350K annually, plus equity

Company

hirify.global builds agentic AI products that automate critical work across the insurance industry.

What you will do

  • Build evaluation frameworks and infrastructure for measuring the accuracy, quality, and reliability of AI agents.
  • Develop golden datasets, benchmarks, and regression suites for real-world insurance workflows and edge cases.
  • Design evaluations for multi-step agent trajectories, tool use, reasoning, and end-to-end task completion.
  • Create automated grading systems using LLM-as-judge methods, deterministic graders, human evaluation workflows, and quality rubrics.
  • Integrate offline and online evaluations into development and release processes to detect regressions and measure improvements.
  • Benchmark frontier and open-weight models across accuracy, latency, cost, and reliability, using results to guide production model selection.

Requirements

  • 5+ years of software engineering experience with hands-on experience building production AI/ML systems.
  • Experience with evaluation frameworks, LLM applications, model benchmarking systems, or applied AI infrastructure.
  • Strong understanding of modern LLMs, agent architectures, evaluation methodologies, and model performance tradeoffs.
  • Strong Python engineering skills and the ability to build reliable production-grade systems.
  • Ability to independently own ambiguous technical problems from research and experimentation through production.
  • Clear written and verbal communication skills.

Nice to have

  • Experience with LLM-as-judge systems, human evaluation, agent trajectory evaluations, or large-scale benchmarking.
  • Experience with open-weight models, fine-tuning, post-training, or model routing.
  • Background in B2B SaaS or 0-to-1 product development.

Culture & Benefits

  • Highly technical environment with significant engineering influence on product direction.
  • Fully covered health, dental, and vision benefits.
  • Meaningful stock options and a company 401(k).
  • Unlimited paid time off and pre-tax commuter benefits.
  • On-site lunch and dinner, team events, and off-sites.

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