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AI Engineer​/Data Scientist

Job in Irvine, Orange County, California, 92713, USA
Listing for: Commercial Bank of California
Full Time position
Listed on 2026-02-14
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 170000 - 220000 USD Yearly USD 170000.00 220000.00 YEAR
Job Description & How to Apply Below

Location: Irvine, CA

Job Type: Full-Time | Exempt | Remote/Hybrid Eligible

Salary Range: $170,000 – $220,000 per year

About Commercial Bank Of California

Commercial Bank of California (CBC) is the largest Latino‑owned bank in California and a certified Minority Depository Institution (MDI). Headquartered in Irvine and founded in 2003, CBC is one of the largest privately held banks in the state, with over $3.5 billion in assets as of December 2025. We are a purpose‑driven financial institution committed to building long‑term relationships and delivering innovative, personalized banking solutions.

Our leadership reflects the diverse communities we serve, and our mission is rooted in empowering entrepreneurs, business owners, and community leaders to thrive.

As a certified MDI, CBC is proud to play a vital role in advancing financial inclusion and economic opportunity. We believe in a higher vision for banking—one that prioritizes trust, collaboration, and community impact. Join us and be part of a team that’s redefining what it means to be a community‑focused, relationship‑driven bank that puts people over profits.

Job Summary

As a Senior AI Engineer/Data Scientist, you will lead the design, development, and deployment of production‑grade AI solutions within our financial services ecosystem. You will bridge the gap between complex data science and scalable software engineering, utilizing Azure AI Foundry to build secure, high‑performing models. A primary focus will be on Intelligent Automation—replacing manual financial workflows with AI‑driven agents and LLM‑powered systems.

Essential

Duties And Responsibilities
  • Design and implement end‑to‑end AI pipelines using Azure AI Foundry (formerly Azure AI Studio), including orchestrating complex AI workflows, building RAG (Retrieval‑Augmented Generation) systems for financial document processing, and deploying large language models.
  • Establish best practices for prompt engineering, model fine‑tuning, and responsible AI implementation across the organization.
  • Identify and automate high‑value banking processes using a combination of traditional ML, generative AI, and agentic systems. This includes automating loan origination workflows, regulatory reporting, document intelligence systems, customer service automation, and compliance monitoring using tools like Azure Document Intelligence, OpenAI models, Claude, and custom solutions.
  • Identify manual processes in banking operations (e.g., KYC, credit scoring, fraud detection) and engineer automated solutions using AI agents and RAG architectures.
  • Leverage Claude Code and other developer‑centric AI tools to accelerate the software development lifecycle (SDLC) and maintain high code quality.
  • Evaluate and fine‑tune Large Language Models (LLMs) like GPT‑4, Claude 4, and Llama 3 for finance‑specific terminology and compliance requirements.
  • Work closely with cybersecurity teams to ensure all AI deployments adhere to banking regulations (GDPR, CCPA, and Basel III standards), implementing robust guardrails and "Human‑in‑the‑Loop" systems.
  • Document solutions, present technical findings, and support knowledge sharing across teams.
  • Create production‑ready AI systems by incorporating an Enterprise‑wide framework, rapidly adapt to emerging AI techniques, and own the lifecycle of models and agents from initial ideation through monitoring and maintenance. Coordinate with cross‑functional data and business teams while retaining technical accountability.
  • Own the complete AI development lifecycle: prototype, product ionize, monitor, and continuously improve models and systems.
  • Rapidly evaluate, adopt, and optimize new AI techniques and platforms as technology evolves.
Minimum Qualifications
  • Technical AI/ML Expertise
  • 7+ years of experience in AI/ML engineering or data science with minimum 10+ IT engineering experience.
  • Bachelor’s degree in computer science, engineering, mathematics, data science, information systems, or equivalent.
  • Deep Learning & LLMs:
    Proven experience with Prompt Engineering, RAG, and fine‑tuning techniques.
  • Cloud Platforms:
    Mastery of Azure AI Foundry, Azure Machine Learning, and Azure OpenAI Service.
  • AI Tooling:
    Hands‑on…
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