AI Scientist/AI Architect
Listed on 2026-07-01
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IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
AI Scientist / AI Architect
Duration: 6-12+ Months Contract
Location:
Irvine, CA, and LA, CA
Number of days onsite: 2-3 days/week in the client's Irvine office, 1 day in their downtown LA office, 1 day remote.
Mandatory Areas- AI/ML Solution Architecture
- LLM & Generative AI Development
- Agent-Based Systems
- Retrieval-Augmented Systems (RAG)
- Enterprise AI Integration
- Python & Backend Development
- LLM / Generative AI Application Development
- Agent-Based AI Systems
- RAG / Vector DB / Embeddings
- API Development & System Integration
- AWS Cloud (Cloud-Native Development)
- CI/CD & Dev Ops Practices
- Observability (Logging, Monitoring, Tracing)
AI-enabled enterprise workflows Marketing / Content generation platforms (nice to have) Financial / Investment domain (preferred based on content use cases)
You AreA 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.
TheOpportunity
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 (RAG, vector search, 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 (APIs, internal tools, 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
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