Principal AI Engineer – Agentic AI / Generative AI | Irvine, CA (Hybrid) | Contract to Hire | AS

Central Business Solutions•Irvine, CA

1d•Hybrid

About The Position

We are seeking a Principal AI Engineer to lead the design and development of next-generation Agentic AI solutions for enterprise applications. This role requires a highly experienced AI engineer with deep expertise in Large Language Models (LLMs), AI Agents, Multi-Agent Systems, Retrieval-Augmented Generation (RAG), and cloud-native AI architectures. You will drive the architecture, development, deployment, and optimization of intelligent AI agents that automate complex business workflows, power enterprise copilots, and integrate seamlessly with enterprise platforms.

Requirements

Bachelor's or master's degree in computer science, Artificial Intelligence, Machine Learning, or related field.
12+ years of software engineering experience.
5+ years building AI/ML applications.
Strong hands-on experience developing AI Agents and Agentic AI solutions.
Experience building production-grade Generative AI applications.
Strong Python programming expertise.
Experience deploying AI applications in AWS.
Excellent architecture and system design skills.

Responsibilities

AI Agent Development: Design, develop, and deploy AI Agents and Multi-Agent Systems for enterprise applications.
Build intelligent AI copilots capable of reasoning, planning, and executing complex business workflows.
Develop agent orchestration frameworks using modern AI technologies.
Implement memory, planning, tool usage, and autonomous decision-making capabilities.
Generative AI Engineering: Design production-grade Generative AI applications using Large Language Models.
Build Retrieval-Augmented Generation (RAG) solutions using enterprise data.
Develop prompt engineering strategies and context management pipelines.
Fine-tune and optimize LLM-powered applications for enterprise use cases.
AI Architecture: Architect scalable AI platforms supporting multiple enterprise applications.
Design AI microservices and API-driven architectures.
Build AI workflows integrating structured and unstructured enterprise data.
Ensure high availability, scalability, security, and observability of AI systems.
Cloud & MLOps: Deploy AI applications on AWS using cloud-native services.
Build containerized AI applications using Docker and Kubernetes.
Develop CI/CD pipelines for AI model deployment.
Monitor model performance, drift, latency, and reliability.
Enterprise Integration: Integrate AI Agents with enterprise applications including CRM, ERP, ITSM, and internal APIs.
Build AI-powered workflow automation solutions.
Collaborate with product, engineering, and business teams to deliver enterprise AI capabilities.
Technical Leadership: Provide technical leadership across AI initiatives.
Mentor engineers on AI architecture and best practices.
Conduct design reviews, code reviews, and architecture reviews.
Evaluate emerging AI technologies and recommend adoption strategies.