Job Description - AI Architect




We are hiring for a Job Role : AI Scientist / AI Architect (Hands-on)



Location: Irvine, CA and LA, CA (2-3 days / week in the client’s Irvine office, 1 day in their downtown LA office, 1 day remote)



Type: Contract-W2






You Are:



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.







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 / agent-oriented AI systems

  • Strong expertise in retrieval-based systems (RAG, vector databases, embeddings, 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 (logging, monitoring, tracing)

  • Experience deploying ML models in production environments

  • Exposure to enterprise AI workflows, automation, and governance models







Mandatory Areas



• AI/ML Solution Architecture



• LLM & Generative AI Development



• Agent-Based Systems



• Retrieval-Augmented Systems (RAG)



• Enterprise AI Integration



________________________________________



Must Have Skills



• Skill 1 – Python & Backend Development



• Skill 2 – LLM / Generative AI Application Development



• Skill 3 – Agent-Based AI Systems



• Skill 4 – RAG / Vector DB / Embeddings



• Skill 5 – API Development & System Integration



• Skill 6 – AWS Cloud (Cloud-Native Development)



• Skill 7 – CI/CD & DevOps Practices



• Skill 8 – Observability (Logging, Monitoring, Tracing)



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