
AI Engineer - Hybrid in Irvine, CA - W2 (No C2C) Posted by Tauqeer
Project Goals
- Utilize AI and machine learning models to provide real-time financial insights and recommendations for retirement planning.
- Develop AI-powered tools that assist brokers in analyzing customer portfolios, risk assessments, and investment strategies.
- Implement AI-driven chatbots and virtual agents to provide customer support and automated financial guidance.
- Optimize data pipelines to integrate structured and unstructured financial data into AI models for better decision-making.
Technical Stack & Responsibilities
- Programming: Develop and maintain AI-enabled applications using Java or Python.
- AI Model Experience: Implement and fine-tune large language models (LLMs) for financial advisory and customer support.
- AI Agent Systems: Build AI-driven agent applications that assist brokers in identifying optimal investment strategies based on historical trends.
- GenAI & RAG Frameworks: Implement Generative AI (GenAI) to enhance customer interactions and Retrieval-Augmented Generation (RAG) frameworks to provide personalized financial insights.
- Cloud Deployment: Develop scalable, cloud-based AI solutions utilizing AWS/Azure AI services.
Preferred Qualifications
- Experience in financial services and retirement planning AI solutions.
- Proficiency in leveraging AI components from existing platforms like Copilot Studio and Appian AI Skills.
Impact of the Role
This role will be crucial in backfilling a critical AI engineering position, ensuring the continued development of AI-driven financial solutions that enhance retirement planning services. The ideal candidate will bring a strong software development background, expertise in modern AI architectures, and the ability to build scalable AI-enabled financial systems.
Project Goals
- Utilize AI and machine learning models to provide real-time financial insights and recommendations for retirement planning.
- Develop AI-powered tools that assist brokers in analyzing customer portfolios, risk assessments, and investment strategies.
- Implement AI-driven chatbots and virtual agents to provide customer support and automated financial guidance.
- Optimize data pipelines to integrate structured and unstructured financial data into AI models for better decision-making.
Technical Stack & Responsibilities
- Programming: Develop and maintain AI-enabled applications using Java or Python.
- AI Model Experience: Implement and fine-tune large language models (LLMs) for financial advisory and customer support.
- AI Agent Systems: Build AI-driven agent applications that assist brokers in identifying optimal investment strategies based on historical trends.
- GenAI & RAG Frameworks: Implement Generative AI (GenAI) to enhance customer interactions and Retrieval-Augmented Generation (RAG) frameworks to provide personalized financial insights.
- Cloud Deployment: Develop scalable, cloud-based AI solutions utilizing AWS/Azure AI services.
Preferred Qualifications
- Experience in financial services and retirement planning AI solutions.
- Proficiency in leveraging AI components from existing platforms like Copilot Studio and Appian AI Skills.
Impact of the Role
This role will be crucial in backfilling a critical AI engineering position, ensuring the continued development of AI-driven financial solutions that enhance retirement planning services. The ideal candidate will bring a strong software development background, expertise in modern AI architectures, and the ability to build scalable AI-enabled financial systems.