10 дней назад
AI Solutions Architect
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Solutions Architect (LLM inference and governance): Architecting customer implementations for Kimchi's autonomous coding agents, multi-model routing, and LLM governance with an accent on inference optimization, cost control, and customer adoption. Focus on configuring agent workspaces, enforcing spending and model-access policies, integrating serverless inference APIs, and translating customer feedback into product improvements.
Location: Remote-first role associated with Atlanta, Boston, New York, and Seattle, United States
Company
operates an automation platform for cloud-native and AI infrastructure, using autonomous decision-making to optimize Kubernetes and production environments.
What you will do
- Lead hands-on customer demos of Kimchi Coding, Kimchi Studio, and Teleport.
- Set up Kimchi Studio workspaces, including worktrees, Slack, repositories, documentation, and agent skills.
- Design and implement governance policies for spending limits, project cost attribution, model routing, and model access.
- Help customers integrate the serverless inference API and optimize model selection and routing for coding, reasoning, and planning workloads.
- Translate customer feedback about agent failures, Studio UX, and governance needs into product input.
Requirements
- Deep hands-on experience deploying, fine-tuning, evaluating, or debugging large language models.
- Experience building or optimizing inference systems and understanding latency, throughput, and total cost of ownership.
- Ability to explain complex inference concepts to non-ML engineers and connect them to business value.
- Commercial and entrepreneurial thinking, including identifying customer expansion opportunities and designing growth strategies.
- Ability to operate effectively in a fast-moving, frequently changing environment.
- Visa sponsorship and work-permit support are not provided.
Culture & Benefits
- Flexible, remote-first global working environment.
- Collaboration with cloud and Kubernetes experts across a global organization.
- Equity options, equipment budget, learning budget, and team-building budget.
- Extra days off and 10% of work time for personal projects or self-improvement.
- Fast-paced workflow, with most feature projects completed in one to four weeks.
Hiring process
- Recruiter screening call.
- Hiring Manager interview followed by one or two additional interviews.
- Executive Culture Check interview; a background check may be conducted at the final stage.
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