Sr. AI Engineer

CalPrivate Bank is advancing data analytics and artificial intelligence capabilities with solutions built for a highly regulated banking environment. This onsite role in Brea, CA combines production AI and analytics engineering with responsible governance, so outcomes can be trusted by employees, leadership, and the organization’s long-term strategy.

Salary: USD 145,000 - 172,000 per year.

What you’ll do

The Senior AI Engineer will translate business needs and strategy into executable AI and analytics solutions, with ownership across development, testing, deployment, monitoring, and ongoing support.

• Design, develop, test, deploy, and maintain AI, generative AI, machine learning, data engineering, and advanced analytics solutions that address business needs across the Bank.
• Partner with data and technology leadership to convert AI and analytics objectives into technical requirements, development priorities, and executable deliverables.
• Build and enhance Snowflake-centered data pipelines, integrations, APIs, and architecture to support analytics, AI applications, and data products.
• Develop generative AI and ML solutions using large language models, including Snowflake Cortex AI, Cortex Search, and Cortex Agents, with capabilities such as RAG, enterprise search, intelligent document processing, workflow automation, and internal knowledge tools where appropriate.
• Create modular AI architectures that support evaluating, integrating, and substituting models and providers to balance performance, security, cost, and operational complexity while minimizing unnecessary vendor dependency.
• Evaluate emerging AI technologies, platforms, models, and vendors, and provide recommendations considering business value, scalability, security, cost, and regulatory considerations.
• Develop prototypes and proofs of concept, then transition viable solutions into stable, production-ready applications with testing, deployment, and monitoring.
• Work with business teams to identify opportunities where AI, automation, or advanced analytics can improve efficiency, reduce manual work, enhance decision-making, and improve client and employee experience.
• Support the Bank’s enterprise data environment, including data quality, accessibility, lineage, integration, and governance.
• Create reusable frameworks, tools, and engineering standards that enable scaling AI capabilities instead of 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, along with ongoing effectiveness.
• Create and maintain technical documentation and inventory records for AI solutions (models, prompts, agents, data sources, integrations, dependencies, and controls) to ensure traceability across the lifecycle, including retirement.
• Collaborate with Information Security, Risk, Compliance, Legal, and other control functions to ensure AI solutions are developed and implemented responsibly and per Bank policies and regulatory expectations.
• Serve as a senior technical resource to the data and analytics team, providing guidance, troubleshooting, and best practices to improve overall AI and engineering capability.
• Build repeatable development and deployment processes to execute objectives efficiently and scale as the Bank grows.
• Communicate complex technical concepts clearly to technical and non-technical stakeholders, including senior leadership.
• Approach development with understanding of data privacy, cybersecurity, model risk, third-party risk, explainability, access controls, human oversight, and regulatory compliance.
• Report suspicious activity to the BSA Officer as appropriate and follow Bank BSA/AML policies by elevating suspicious activity to the BSA Officer.

What you bring

• 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, and workflow orchestration or model/API integration.
• Strong hands-on experience with Snowflake, including data engineering, data pipelines, security and access patterns, integrations, and building production workloads.
• 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 ability to operate independently while collaborating across teams.
• Experience working with sensitive or highly regulated data is strongly preferred; banking, financial services, fintech, or another regulated industry is highly desirable.
• Accountability, integrity, and consistency.
• Collaboration with transparency and follow-through.
• Professional approach, calm under pressure, and solutions-oriented mindset.
• Data-driven decision-making with a client-first perspective.

Technology stack

• Python, SQL
• Snowflake, Snowpark
• Cortex AI, Cortex Search, Cortex Agents
• Retrieval-augmented generation (RAG), enterprise search, intelligent document processing, workflow automation
• Large language models, generative AI, machine learning
• Embeddings, vector databases, AI agents, workflow orchestration, model/API integration
• Microsoft Azure, Azure Functions, Azure Storage/Blob Storage
• ETL/ELT, APIs, relational databases, data warehouses/lakehouses
• Git, GitHub, CI/CD, CI, CD
• Observability, dynamic tables, external stages, streams/tasks

Location

Onsite: Brea, CA

Los Angeles, Orange County, San Diego

Responsible AI and banking environment

In financial services, AI must be implemented thoughtfully. This role requires a strong understanding of data privacy, cybersecurity, model risk, third-party risk, explainability, access controls, human oversight, and regulatory compliance. The focus is on building sustainable capabilities employees and leadership can trust, aligned to the Bank’s long-term strategy.

AML/CFT and compliance responsibilities

• The position includes direct or indirect interaction with customers and other employees, including BSA/AML responsibilities.
• The employee may examine information and documents produced by other employees related to BSA, and must report suspicious activity to the BSA Officer as appropriate.
• The employee is responsible for understanding and following the Bank’s BSA/AML policies, including elevating suspicious activity to the BSA Officer.

Physical demands

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