AI/ML Architect/GenAI Architect
Pathblend Solutions
LOS ANGELES · US
LOS ANGELES · US
AI Solutions Architect
Summary by AIEngineer.careers
AI Solutions Architect is a AI Solutions Architect role (full-time). with Cast AI. in BOSTON, US. Compensation shown: $143K–$209K (est.). Imported listing (source: jobs-radar.com). Apply on the employer's site (jobs-radar.com).
Imported listing (source: jobs-radar.com) · Apply on jobs-radar.com
BOSTON · US
$143K–$209K (est.)
Full-time
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from jobs-radar.com
Cast AI is hiring a founding customer-facing AI Solutions Architect for its Kimchi product. The role focuses on designing and deploying multi-model LLM workflows, autonomous agents, inference optimization, and LLM governance for customers. You will act as the technical bridge between customers and the product, shaping both solutions and the platform's direction.
Responsibilities
- Design multi-model LLM workflows and autonomous agent solutions for customers
- Lead inference optimization and LLM governance engagements
- Serve as the founding customer-facing technical engineer for Kimchi
- Translate customer requirements into product and platform improvements
Requirements
- Experience architecting LLM or generative AI solutions for customers
- Strong understanding of inference optimization and model deployment
- Customer-facing engineering or solutions architecture background
- Familiarity with LLM governance and safety practices
Nice to Have
- Experience in early-stage or founding engineering roles
- Background with multi-model orchestration frameworks
Tech Stack
Autonomous AgentsInference OptimizationLLMLLM Governance
Cast AI
Miami · US · 346+ employees
Cast AI is a cloud-native and AI workload automation platform focused on Kubernetes optimization. Its platform automates resource management and orchestration to improve application reliability and performance while reducing cloud costs.
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