icims
AI Engineer
East West Bank
Pasadena, USA
Full-time
Senior · 10+ years experience
Onsite
USD 125000-250000 yearly / year
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Since 1973, East West Bank has served as a pathway to success. With over 110 locations across the U.S. and Asia, we are the premier financial bridge between the East and West. Our teams of experienced, multi-cultural professionals help guide businesses and community members on both sides of the Pacific looking to explore new markets and create new opportunities, and our sustained growth and expertise in industries like real estate, entertainment and media, private equity and venture capital, and high-tech help build sustainable businesses and expand our associates’ potential for career advancement.
Headquartered in California, East West Bank (Nasdaq: EWBC) is a top-performing commercial bank with a strong foundation, an enterprising spirit and a commitment to absolute integrity.
East West Bank gives people the confidence to reach further.
East West Bank is seeking an experienced Senior AI Engineering to design, build, and operationalize enterprise-grade AI and Generative AI solutions across the Bank.
This senior technical leader will translate emerging AI capabilities into secure, scalable, production-ready banking applications that improve operational efficiency, risk management, customer experience, and employee productivity.
The role is expected to be hands-on at the outset while helping establish foundational AI engineering capabilities, operating standards, and a small, high-performing AI engineering team.
- Design, develop, and deploy enterprise AI and Generative AI applications for prioritized banking use cases (e.g., customer service, fraud detection, document processing, knowledge management, and operational efficiency)
- Architect LLM-enabled solutions spanning retrieval-augmented generation, vector search, agentic workflows, MCP, model orchestration, tool/function calling, and human-in-the-loop controls.
- Build production-grade services and APIs using Python, FastAPI or Flask, Azure OpenAI, Azure ML, Databricks, ADLS, and modern cloud-native patterns.
- Integrate AI capabilities into enterprise applications, developer workflows, knowledge management platforms, automation, analytics, and decision-support processes.
- Establish engineering practices for CI/CD, testing, model evaluation, observability, performance optimization, security, and responsible AI controls.
- Establish reusable AI engineering frameworks, reference architectures, code standards, deployment patterns, and governance controls to accelerate enterprise adoption.
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