AI Lead Engineer / AI Architect

Job Description

Role: AI Lead Engineer / AI Architect

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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)

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Duration: Long term Contract

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\n Job Description

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:A highly skilled hands-on AI Lead Engineer / Architect with at least 12+ years of experience in AI/ML, Data Engineering, 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

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\n The Opportunit

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• y:Design and develop scalable AI/ML pipelines and intelligent applications aligned with enterprise standar

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• dsBuild agent-based AI workflows, automation systems, and retrieval-based architectures (RAG, vector search, embedding

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• s)Architect and implement LLM orchestration layers supporting content ideation, drafting, and editing workflo

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• wsLead integration of AI solutions with backend systems and enterprise platforms (APIs, internal tools, data platform

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• s)Partner with product, marketing, and business stakeholders to translate requirements into AI-driven solutio

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• nsProvide architectural leadership, guide offshore teams, and ensure delivery aligned with scalability, security, and governance standar

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\n What You Ne

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• ed:At least 8+ years of experience in AI/ML, Data Science, or Software Engineer

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• ingStrong Python backend development experie

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• nceHands-on experience with LLM-enabled applications and Generative

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• AIExperience building agent-based / agent-oriented AI syst

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• emsStrong expertise in retrieval-based systems (RAG, vector databases, embeddings, indexi

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• ng)Experience with API development and backend system integrat

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• ionAWS cloud-native development experie

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• nceExperience with CI/CD pipelines and environment managem

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• entStrong understanding of observability (logging, monitoring, traci

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• ng)Experience deploying ML models in production environme

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• ntsExposure to enterprise AI workflows, automation, and governance mod

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\n Mandatory A

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• reasAI/ML Solution Architec

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• tureLLM & Generative AI Develop

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• mentAgent-Based Sys

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• temsRetrieval-Augmented Systems (

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• RAG)Enterprise AI Integra

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tion
\n Must Have S

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• killsSkill 1 – Python & Backend Develo

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• pmentSkill 2 – LLM / Generative AI Application Develo

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• pmentSkill 3 – Agent-Based AI Sy

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• stemsSkill 4 – RAG / Vector DB / Embed

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• dingsSkill 5 – API Development & System Integr

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• ationSkill 6 – AWS Cloud (Cloud-Native Develop

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• ment)Skill 7 – CI/CD & DevOps Prac

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• ticesSkill 8 – Observability (Logging, Monitoring, Tra

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cing)
\n Domain Experience (I

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• f any)AI-enabled enterprise wor

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• kflowsMarketing / Content generation platforms (nice to

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• have)Financial / Investment domain (preferred based on content use

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cases)
\n Must Have Certifi

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• cationsNot mandatory (AWS / ML / AI certifications are good t

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o have)