Client-Embedded AI Engineer: Build & Deploy Production AI

Cadre AI; San Diego (CA); Hybride; USD 150 000 - 210 000; Plein temps

Résumé du poste

Cadre AI is seeking an experienced Forward Deployed AI Engineer to partner directly with clients, write production-grade code, and architect AI systems. You will own both strategy and execution, embedding with client teams to identify high-leverage AI opportunities and deliver measurable results across multiple domains.

You will build LLM/RAG pipelines, agent orchestration, and production services using Claude Code, Cursor, Codex, and Langfuse while maintaining data quality and secure cloud

Qualifications

• 3+ years building software, with 2+ years in AI/ML production.
• Shipped LLM-powered products to real users.
• Proficient in TypeScript & Python; familiar with React/Next.js, PostgreSQL, and cloud platforms.
• Ability to explain ROI to executives and mentor junior engineers.
• AI-native worker comfortable with ambiguity and fast-paced delivery.

Responsabilités

• Embed with clients across private equity, lending, real estate, and SaaS to map operations and identify AI use cases that move the business.
• Design and deploy LLM/RAG pipelines, agent orchestration systems, conversational AI, document intelligence, and predictive analytics.
• Lead end-to-end client delivery from discovery through deployment and post-launch optimization.
• Mentor junior engineers through pair programming, code reviews, and hands-on coaching.
• Present to C-suite stakeholders, translating trade-offs into concrete, measurable outcomes.

Description du poste

Cadre AI is seeking an experienced Forward Deployed AI Engineer to partner directly with clients, write production-grade code, and architect AI systems. You will own both strategy and execution, embedding with client teams to identify high-leverage AI opportunities and deliver measurable results across multiple domains.

You will build LLM/RAG pipelines, agent orchestration, and production services using Claude Code, Cursor, Codex, and Langfuse while maintaining data quality and secure cloud