AI Solutions Architect

🔥 0 minutes ago

🗽 New York, Massachusetts, +2 more states – Remote

🗽 New York – Remote 🍂 Massachusetts – Remote ☕ Washington – Remote 🍑 Georgia – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 12%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Cast AI

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2019

☁️ SaaS

🤖 Artificial Intelligence

🤝 B2B

SaaS • Artificial Intelligence • B2B

Cast AI is a SaaS platform that automates Kubernetes application performance, infrastructure, and cost optimization for cloud-native teams. It connects to EKS/AKS/GKE and on-prem clusters with no code changes, uses predictive models and runtime signals to rightsize pods, scale nodes, optimize GPUs and Spot instances, and run approved self-healing runbooks to maintain reliability and reduce cloud spend. Cast AI targets platform, SRE, and FinOps teams and supports AI/LLM workloads, GPU optimization, and real-time workload placement and cost intelligence.

📋 Description

• Serve as the founding customer-facing engineer for the Kimchi product within Customer Success • Architect and execute the growth strategy to scale Kimchi adoption and create revenue expansion opportunities • Lead hands-on demos of Kimchi Coding, Studio, and Teleport • Set up Kimchi Studio workspaces in customer environments • Configure worktrees, Slack, repositories, documentation integrations, and agent skills • Design and implement customer governance policies for spending limits, project cost attribution, and model routing • Integrate Kimchi's serverless inference API • Optimize model selection and routing for coding, reasoning, and planning workloads • Translate customer feedback into product input regarding agent failures, Studio UX, and governance policies

🎯 Requirements

• Deep hands-on experience with LLMs, including deploying, fine-tuning, evaluating, or debugging failure modes • Experience operating in a fast-moving, change-prone environment • Experience building or optimizing inference systems • Understanding of latency, throughput, and total cost of ownership • Ability to explain complex inference concepts to non-ML engineers • Commercial understanding of revenue expansion and customer expansion opportunities • Ability to combine technical excellence with entrepreneurial growth thinking • No visa sponsorship or work permit provided

🏖️ Benefits

• Flexible, remote-first global environment • Equity options • 10% of work time for personal projects or self-improvement • Learning budget for professional and personal development, including international conferences and courses • Team-building budget and company events • Equipment budget • Extra days off • Background check conducted through Checkr as part of the hiring process

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