Hands-on AI Architect to design and build production-ready LLM and agent-based AI solutions. Responsibilities include developing Python backends, retrieval-augmented (RAG) systems with vector DBs and embeddings, API and cloud-native (AWS) integrations, CI/CD, observability, and deploying ML models while guiding enterprise AI governance and workflows.
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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