Sr. AI Engineer

CalPrivate Bank is building next-generation data analytics and artificial intelligence capabilities in a highly regulated banking environment. As a Senior AI Engineer, you will translate business needs and emerging technologies into production-ready AI and analytics solutions, with a Snowflake-centered foundation and responsible AI standards designed for long-term trust.

This onsite role in Los Angeles, Orange County, or San Diego, CA (San Diego listed) supports the Bank’s enterprise data environment while expanding generative AI and automation capabilities that improve efficiency, decision-making, and the client and employee experience.

Responsibilities

• Design, develop, test, deploy, and maintain AI, generative AI, machine learning, data engineering, and advanced analytics solutions that address meaningful business needs across the Bank.
• Partner with data and technology leadership to translate strategic AI and analytics objectives into technical requirements, development priorities, and executable solutions.
• Build and enhance Snowflake-centered data pipelines, integrations, APIs, and architecture supporting analytics, AI applications, and data products.
• Develop generative AI solutions using Snowflake Cortex AI, Cortex Search, Cortex Agents, retrieval-augmented generation (RAG), enterprise search, intelligent document processing, workflow automation, and internal knowledge tools where appropriate.
• Create flexible, modular AI architectures that allow evaluation, integration, and substitution of different AI models and providers where appropriate, balancing performance, security, cost, and operational complexity while minimizing unnecessary vendor dependencies.
• Evaluate emerging AI technologies, platforms, models, and vendors, and provide recommendations grounded in business value, scalability, security, cost, and regulatory considerations.
• Develop prototypes and proofs of concept, then transition viable solutions into stable, production-ready applications with ownership across testing, deployment, monitoring, and ongoing support.
• Partner with business teams to identify opportunities for AI, automation, or advanced analytics that reduce manual work, improve efficiency, strengthen decision-making, and enhance client and employee experience.
• Support ongoing development of the Bank’s enterprise data environment, including data quality, accessibility, lineage, integration, and governance.
• Create reusable frameworks, tools, and engineering standards so the team can expand AI capabilities efficiently rather than building isolated solutions.
• Establish testing, evaluation, monitoring, and observability for AI solutions, including quality, accuracy, reliability, performance, security, cost, and model or data drift where applicable.
• Develop and maintain technical documentation and inventory records for AI solutions, including models, prompts, agents, data sources, integrations, dependencies, and controls to support traceability through the lifecycle.
• Collaborate with Information Security, Risk, Compliance, Legal, and other control functions to ensure AI solutions are developed and implemented responsibly and in accordance with Bank policies and regulatory expectations.
• Serve as a senior technical resource to the data and analytics team by providing guidance, troubleshooting complex technical issues, sharing best practices, and raising overall AI and engineering capability.
• Help create repeatable development and deployment processes to execute efficiently and scale capabilities as the Bank grows.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders, including senior leadership.

Responsible AI and Banking Environment

• Approach development with a strong understanding of data privacy, cybersecurity, model risk, third-party risk, explainability, access controls, human oversight, and regulatory compliance.
• Build sustainable capabilities that employees and leadership can trust and that meaningfully support the Bank’s long-term strategy.

AML/CFT/Compliance Responsibilities

• Includes responsibilities relating to BSA/AML due to direct or indirect interaction with customers and other employees.
• Opportunity to examine and view information and documents produced by other employees relating to BSA.
• Obligation to report suspicious activity to the BSA Officer as appropriate.
• Responsible for understanding and following the Bank’s BSA/AML policies, including elevating suspicious activity to the BSA Officer.
• Required to understand and follow the Bank’s compliance program BSA/AML policies, including elevating suspicious activity to the BSA Officer.

Requirements

• Advanced experience in AI engineering, machine learning engineering, data engineering, applied data science, or a closely related discipline.
• Strong proficiency in Python and SQL, with experience applying modern software and data engineering practices.
• Demonstrated experience building and deploying production AI, generative AI, data, and analytics applications.
• Hands-on experience with generative AI technologies, large language models, prompt engineering, embeddings, vector databases, RAG architectures, AI agents or workflow orchestration, and model/API integration.
• Strong hands-on experience with Snowflake, including data engineering, data pipelines, security and access patterns, integrations, and building production workloads on the platform.
• Experience with Snowpark, Cortex AI, Cortex Search, Cortex Agents, external stages, streams/tasks, dynamic tables, or related Snowflake capabilities is highly desirable.
• Hands-on experience integrating data and AI solutions with Microsoft Azure, particularly Azure Functions and Azure Storage/Blob Storage.
• Strong understanding of data architecture, ETL/ELT pipelines, APIs, relational databases, data warehouses/lakehouses, and structured and unstructured data.
• Experience with modern software engineering and DevOps practices, including Git/GitHub, branching and pull-request workflows, automated testing, CI/CD, environment management, code review, and controlled production deployment.
• Ability to assess business problems and determine when AI is, and when it is not, the appropriate solution.
• Strong analytical, problem-solving, and communication skills with the ability to operate independently while collaborating effectively across teams.
• Experience working with sensitive or highly regulated data is strongly preferred; banking, financial services, fintech, or another regulated industry is highly desirable.
• Leads with accountability, integrity, and consistency; thrives in a collaborative environment with transparency and follow-through.
• Models professionalism, calm under pressure, and a solutions-oriented mindset; embraces data-driven decision-making with a client-first perspective; embodies CalPrivate culture, heart for client, excellence in service, and deep commitment to the Bank and its people.

Technologies

Python, SQL, Snowflake, Snowpark, Cortex AI, Cortex Search, Cortex Agents, retrieval-augmented generation (RAG), large language models, prompt engineering, embeddings, vector databases, enterprise search, intelligent document processing, workflow automation, AI agents, workflow orchestration, model/API integration, Microsoft Azure, Azure Functions, Azure Storage/Blob Storage, ETL/ELT pipelines, APIs, relational databases, data warehouses/lakehouses, Git, GitHub, CI/CD, external stages, streams/tasks, dynamic tables.

Physical Demands

• May require some travel to support team, department, and initiatives.
• Ability to sit or stand for extended periods, use a keyboard/mouse, and walk to and from workstations.
• Ability to frequently lift or move up to 10 lbs and occasionally lift or move 50 lbs.
• Specific vision abilities required: close vision and ability to adjust focus.

Compensation: USD 145,000 to 172,000 per year.