What are the responsibilities and job description for the Lead AI Engineer - AI & Credit Analytics position at ChatGPT Jobs?
Job Description
Job Information Extract
Lead AI Engineer - AI & Credit Analytics
Company: Experian
Location: Costa Mesa, CA
Work Arrangement: On-site, Remote, Hybrid
Machine Learning & Artificial Intelligence
Job Summary
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Machine Learning
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Lead AI Engineer role responsible for building scalable, production-grade AI systems to automate and enhance credit analytics and decisioning workflows. The position involves developing AI solutions across the credit lifecycle, implementing LLMOps and GenAI practices, and embedding AI into existing platforms.
Key Responsibilities
Job Information Extract
Lead AI Engineer - AI & Credit Analytics
Company: Experian
Location: Costa Mesa, CA
Work Arrangement: On-site, Remote, Hybrid
Machine Learning & Artificial Intelligence
Job Summary
Discover more
Text & Instant Messaging
Machine Learning
Books & Literature
Lead AI Engineer role responsible for building scalable, production-grade AI systems to automate and enhance credit analytics and decisioning workflows. The position involves developing AI solutions across the credit lifecycle, implementing LLMOps and GenAI practices, and embedding AI into existing platforms.
Key Responsibilities
- Develop and integrate AI solutions across the credit lifecycle (origination, underwriting, limit setting, portfolio monitoring, and model validation).
- Design and implement evaluation and guardrail frameworks to ensure response accuracy, reduce hallucinations, and support human-in-the-loop review.
- Develop and operate enterprise-grade AI services focusing on scalability, security, reliability, and performance optimization.
- Implement LLMOps and GenAI operational practices, including prompt management, model versioning, monitoring, CI/CD pipelines, and observability.
- Partner with analytics, engineering, and product teams to embed AI into existing platforms.
- Evaluate and adopt modern orchestration frameworks and cloud-native AI tools (e.g., LangGraph, AWS services).
- Education: Master's degree in Computer Science, Data Science, or a related quantitative field (or equivalent experience).
- Experience: 8–10 years of professional experience in data science, machine learning, or AI engineering.
- Domain Expertise: Experience in financial services, specifically credit, lending, risk, or analytics-driven decisioning.
- Compliance: Familiarity with regulated environments, data governance, model risk management, and responsible AI practices.
- Technical Skills: Hands-on experience with Generative AI, LLMs, RAG, prompt design, and system optimization.
- Languages: Proficiency in Python and SQL; familiarity with modern Generative AI frameworks.
- Reports to: Senior Director, Data Modeling
- Compensation: Great compensation package including a bonus plan.
- Benefits: Comprehensive health (medical, dental, vision), matching 401K, and flexible time off (vacation, sick, volunteer hours).