2 дня назад
AI Engineer
300 000 - 350 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
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
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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