обновлено 4 дня назад
Senior Applied AI Engineer
167 300 - 245 355$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Applied AI Engineer (LLM systems/cybersecurity): Building applied AI research systems, agent evaluations, prototypes, APIs, and production integrations with an accent on measurable agent behavior, model selection, reliability, and cost-performance tradeoffs. Focus on designing self-improving agent loops, evaluating hosted and self-hosted models, optimizing inference workflows, and transferring validated systems into production.
Location: Colorado, United States
Salary: $167,300–$245,355 USD annually base pay for Colorado and other listed U.S. markets
Company
provides human- and agent-centric cybersecurity solutions that protect people, data, and AI workflows across email, cloud, and collaboration tools.
What you will do
- Lead applied AI research projects from question framing and baseline creation through experimentation, measurement, and actionable decisions.
- Build self-improving agent systems that run evaluation loops, recover from failures, and support long-running tasks.
- Extend evaluation platforms with task suites, regression checks, and measurements for quality, cost, and speed.
- Work with third-party model APIs and open-weight models deployed on company GPU infrastructure, including fine-tuning and efficient serving initiatives.
- Build prototypes, playgrounds, and APIs, then advise production teams on AI integration, monitoring, and system understanding.
- Mentor engineers and collaborate with stakeholders to turn real operational problems into valuable research.
Requirements
- 5+ years of experience building software and ML systems; 7+ years preferred.
- Recent hands-on experience taking LLM systems beyond the prototype stage.
- Daily experience with Claude Code, Cursor, or similar coding agents while maintaining high standards for correctness and testing.
- Strong Python skills and solid machine learning fundamentals.
- Experience with third-party model APIs, open-weight models, production agents, and evaluation systems.
- Familiarity with Kubernetes inference platforms, Flyte, LiteLLM, Langfuse, and internal evaluation and tracing tools.
Nice to have
- Experience fine-tuning or serving open-weight models.
- Experience with automated prompt and pipeline optimization, multi-GPU serving, MCP, or tool protocols.
- Cybersecurity experience in areas such as phishing or threat detection.
- Open-source contributions or research publications.
Culture & Benefits
- Flexible work environment and global collaboration opportunities.
- Competitive compensation and comprehensive benefits.
- Flexible time off, a well-being program, two paid Wellbeing Days, and two paid Volunteer Days per year.
- Three-week Work from Anywhere option and annual wellness and community outreach days.
- Career development and recognition programs.
Hiring process
- Submit an application with supporting information.
- Accommodation is available during the application or interview process upon request.
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