Enterprise AI Architect: LLM, RAG & Automation

Ethereum Technologies; Santa Clara (CA); On-site; USD 180,000 - 230,000; Full time

Job summary

Ethereum Technologies in Santa Clara (CA) seeks a seasoned data/AI engineer to design enterprise-grade solutions for sales, marketing, and product research. You will translate business requirements into scalable data and AI specifications and drive implementations end-to-end.

Responsibilities include building AI/ML pipelines, integrating with orchestration APIs, and developing LLM-powered applications and RAG retrieval systems, while adhering to enterprise architecture standards.

Qualifications

• Translate business requirements into data/AI solutions.
• Align with enterprise architecture standards and production readiness.
• Collaborate with cross-functional teams to deliver features.

Responsibilities

• Translate business requirements into data/AI/ML technical requirements.
• Ensure solutions align with long-term production standards and enterprise architecture guidelines at CG.
• Coordinate with cross-functional teams and business stakeholders on feature development, prioritization, and delivery.
• Design and document: AI/ML pipelines for data ingestion and integration with orchestration APIs and backend systems.
• Agent-based / Agentic AI workflows and automation systems.
• LLM-powered applications, including prompt engineering and structured outputs.
• RAG solutions, including vector search, embeddings, indexing, and retrieval pipelines.

Skills

Data engineering

AI/ML pipeline design

LLM integration

RAG architectures

Prompt engineering

Job description

Ethereum Technologies in Santa Clara (CA) seeks a seasoned data/AI engineer to design enterprise-grade solutions for sales, marketing, and product research. You will translate business requirements into scalable data and AI specifications and drive implementations end-to-end.

Responsibilities include building AI/ML pipelines, integrating with orchestration APIs, and developing LLM-powered applications and RAG retrieval systems, while adhering to enterprise architecture standards.