AI Solutions Architect

Cast AI

. Serve as the founding customer-facing engineer for the Kimchi product within Customer Success .

Posted 11/4/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and optimizing LLMs while effectively translating complex technical concepts for non-technical stakeholders. Combines technical excellence with a strong commercial understanding to drive customer success and revenue expansion.

Highest-signal resume keywords

LLM DeploymentInference System OptimizationCustomer Governance Policy DesignRevenue Expansion StrategyTechnical Communication

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

LLM Fine-TuningModel EvaluationDebugging Failure ModesLatency UnderstandingThroughput AnalysisTotal Cost of OwnershipServerless Inference API IntegrationModel Selection OptimizationWorkspace ConfigurationDocumentation Integration

Soft Skills

Entrepreneurial Growth ThinkingCustomer Feedback TranslationAdaptability in Fast-Moving Environments

Tools & Technologies

Kimchi CodingKimchi StudioTeleportSlackAgent Skills

Industry Keywords

Customer SuccessRevenue ExpansionGovernance PoliciesProject Cost AttributionModel Routing

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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