AI Engineer
East West Bank2 years ago
Pasadena, CA, USAStaff+
Base Salary
$125k - $250k/yr
Responsibilities
- Design, develop, and deploy enterprise AI and Generative AI applications for prioritized banking use cases.
- Architect LLM-enabled solutions using 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 cloud-native patterns.
- Integrate AI capabilities into enterprise applications, developer workflows, knowledge management, automation, analytics, and decision-support processes.
- Establish engineering practices for CI/CD, testing, model evaluation, observability, performance optimization, security, and responsible AI controls.
- Create reusable AI engineering frameworks, reference architectures, code standards, deployment patterns, and governance controls.
- Partner with business, data, cybersecurity, risk, compliance, legal, and vendor teams to meet regulatory, privacy, auditability, and operational risk expectations.
- Prototype with stakeholders, convert pilots into scalable implementations, and define adoption and impact metrics.
- Evaluate LLM platforms for accuracy, latency, cost, security, explainability, and regulated-enterprise suitability.
- Support hiring, mentoring, and day-to-day technical leadership of AI engineers and cross-functional delivery teams.
- Advise leadership on emerging AI technologies, opportunities, risks, and implementation tradeoffs.
Requirements
- Bachelor’s degree in Computer Science, Engineering, Data Science, AI/ML, or equivalent practical experience; an advanced degree is preferred.
- 10+ years of progressive experience in software engineering, AI engineering, platform engineering, or related technology leadership roles, including production AI delivery.
- Experience leading AI, data, automation, or emerging technology initiatives from strategy and experimentation through production delivery.
- Strong hands-on experience with Python, API design, microservices, cloud architecture, distributed systems, data pipelines, CI/CD, testing, observability, and secure software delivery.
- Deep experience with 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.
- Hands-on experience with 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.
- Understanding of Responsible AI, model governance, prompt-injection risks, data privacy, access controls, traceability, and production controls.
- Experience in financial services, banking, fintech, insurance, or another regulated industry, including 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 and experience defining AI roadmaps, operating models, standards, adoption plans, and success metrics.
- Preferred qualifications include a master’s degree, experience establishing AI engineering teams and enterprise AI standards, AI vendor evaluation experience, familiarity with model risk and vendor risk management, privacy impact assessments, MLOps/LLMOps, AI monitoring, evaluation pipelines, model/prompt registries, and production incident management.
Tech Stack
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