Senior AI Engineering

Overview

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.

Responsibilities

• 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
• Partner with business, data, cybersecurity, risk, compliance, legal, and vendor teams to ensure solutions meet regulatory, privacy, auditability, and operational risk expectations
• Prototype rapidly with stakeholders, convert pilots into scalable implementations, and define measurable adoption and impact metrics
• Evaluate LLM platforms for accuracy, latency, cost, security, explainability, and fit for regulated enterprise use cases
• Support hiring, mentoring, and day-to-day technical leadership of AI engineers and cross-functional delivery teams
• Stay current with emerging AI technologies and advise leadership on practical opportunities, risks, and implementation tradeoffs
• Perform other duties as assigned

AI Fluency & Hands-On LLM Skills

• Hands-on experience with major LLM platforms, including OpenAI ChatGPT/Codex, Anthropic Claude, Google Gemini, Microsoft Copilot/Azure OpenAI, AWS Bedrock, and open-source models such as Llama or Mistral
• Practical experience with prompt engineering, RAG, embeddings, vector databases, LLM orchestration frameworks, agentic workflows, evaluation frameworks, and hallucination mitigation
• Ability to design AI applications that include data protection, source validation, access control, logging, monitoring, traceability, and human review where appropriate
• Strong understanding of Responsible AI, model governance, prompt-injection risks, data privacy, and production controls for LLM-enabled solutions

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience; advanced degree preferred
• 10+ years of progressive experience in software engineering, AI engineering, platform engineering or related technology leadership roles, including experience delivering production AI solutions
• Proven experience leading AI, data, automation, or emerging technology initiatives from strategy and experimentation through production delivery
• Strong hands-on engineering background in Python, API design, microservices, cloud architecture, distributed systems, data pipelines, CI/CD, testing, observability, and secure software delivery
• Deep experience with the Azure ecosystem, including Azure OpenAI, Azure ML, Databricks, ADLS, Azure AI Search, and related enterprise integration patterns
• Experience with LLM frameworks and tooling such as LangChain, LlamaIndex, Semantic Kernel, vector databases, model registries, evaluation frameworks, and monitoring/observability tools
• Strong process and data discipline, including data quality, lineage, metadata, workflow design, controls, operational risk, and measurable business outcomes
• Experience in financial services, banking, fintech, insurance, or another regulated industry with strong understanding of compliance, auditability, risk management, and governance
• Ability to lead cross-functional teams, influence senior stakeholders, mentor engineers, and translate complex AI capabilities into practical business solutions
• Strong executive communication skills, including the ability to define AI roadmaps, operating models, standards, adoption plans, and success metrics

Preferred Qualifications

• Master's degree in AI, Computer Science, Data Science, Engineering, or a related field
• Experience establishing AI engineering teams, platforms, reusable delivery patterns, and enterprise AI standards
• Experience with copilots, enterprise search, intelligent document processing, workflow automation, and AI-enabled knowledge management
• Experience driving AI vendor evaluation and selection processes within regulated environments
• Familiarity with model risk management, third-party/vendor risk, privacy impact assessments, and regulated technology delivery
• Experience with MLOps/LLMOps, AI monitoring, evaluation pipelines, model/prompt registries, and production incident management
• Track record of mentoring senior engineers and building high-performing technical teams

Compensation

The base pay range for this position is USD $150,000.00/Yr. - USD $275,000.00/Yr. Exact offers will be determined based on job-related knowledge, skills, experience, and location.