AI Scientist / AI Architect (Hands-On)

Irvine, California | Contract

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AI Scientist / AI Architect (Hands-On) (Hybrid, 4 days onsite) (4 open roles)
Location: Irvine, CA 92618 (3 days) & Los Angeles, CA (1 day) 90013

Length: 6  month contract (potential extension)

Overview:

A highly skilled, hands-on AI Scientist / Architect with at least 8+ years of experience in AI/ML, Data Science, or Software Engineering. You bring strong expertise in designing and building scalable, production-ready AI solutions, with deep hands-on experience in LLM-enabled applications, agent-based systems, and cloud-native architectures. You are comfortable working closely with business stakeholders and leading AI-driven innovation initiatives in an enterprise environment.

Responsibilities: 

  • Design and develop scalable AI/ML pipelines and intelligent applications aligned with enterprise standards
  • Build agent-based AI workflows, automation systems, and retrieval-based architectures including RAG, vector search, and embeddings
  • Architect and implement LLM orchestration layers supporting content ideation, drafting, and editing workflows
  • Lead integration of AI solutions with backend systems and enterprise platforms including APIs, internal tools, and data platforms
  • Partner with product, marketing, and business stakeholders to translate requirements into AI-driven solutions
  • Provide architectural leadership, guide offshore teams, and ensure delivery aligned with scalability, security, and governance standards

What You Need:

  • At least 8+ years of experience in AI/ML, Data Science, or Software Engineering
  • Strong Python backend development experience
  • Hands-on experience with LLM-enabled applications and Generative AI
  • Experience building agent-based and agent-oriented AI systems
  • Strong expertise in retrieval-based systems including RAG, vector databases, embeddings, and indexing
  • Experience with API development and backend system integration
  • AWS cloud-native development experience
  • Experience with CI/CD pipelines and environment management
  • Strong understanding of observability including logging, monitoring, and tracing
  • Experience deploying ML models in production environments
  • Exposure to enterprise AI workflows, automation, and governance models

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