CalPrivate Bank is advancing its data analytics and artificial intelligence capabilities in a highly regulated banking environment, with a focus on responsible governance and production-ready delivery. The Senior AI Engineer role translates business needs and strategy into executable AI, generative AI, and analytics solutions, with a Snowflake-centered foundation and model workflows designed for trust and scalability.
This position is based onsite in Brea, CA, with an annual salary range of USD 145,000 - 172,000. The role supports the Bank’s enterprise data environment while building reusable engineering standards and evaluation practices for AI solutions.
Key Responsibilities
- Design, develop, test, deploy, and maintain AI, generative AI, machine learning, data engineering, and advanced analytics solutions aligned to business needs.
- Partner with data and technology leadership to convert strategic AI and analytics goals into technical requirements, development priorities, and implementable solutions.
- Build and improve Snowflake-centered data pipelines, integrations, APIs, and architectures that support analytics, AI applications, and data products.
- Develop solutions using large language models and generative AI, including 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 modular AI architectures that enable evaluation, integration, and substitution of AI models and providers while balancing performance, security, cost, and operational complexity.
- Evaluate emerging AI technologies, platforms, models, and vendors, then recommend options based on business value, scalability, security, cost, and regulatory considerations.
- Develop prototypes and proofs of concept and transition viable solutions into stable, production-ready applications, including testing, deployment, monitoring, and ongoing support.
- Partner with business teams to identify where AI, automation, or advanced analytics can improve efficiency, reduce manual work, enhance decision-making, or improve client and employee experience.
- Support the enterprise data environment, including data quality, accessibility, lineage, integration, and governance.
- Create reusable frameworks, tools, and engineering standards that help the Bank expand AI capabilities without isolated one-off solutions.
- Establish testing, evaluation, monitoring, and observability for AI solutions, including quality, accuracy, reliability, performance, security, cost, and drift where applicable.
- Maintain technical documentation and inventory records covering models, prompts, agents, data sources, integrations, dependencies, and controls to support traceability across lifecycle stages.
- Collaborate with Information Security, Risk, Compliance, Legal, and other control functions to ensure responsible development and implementation in line with Bank policies and regulatory expectations.
- Act as a senior technical resource to the broader data and analytics team through guidance, troubleshooting, and best-practice sharing.
- Help define repeatable development and deployment processes that support efficient execution and scaling as the Bank grows.
- Explain complex technical concepts to both technical and non-technical stakeholders, including senior leadership.
- Apply expertise in 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 the Bank’s BSA/AML policies, escalating 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 including large language models, prompt engineering, embeddings, vector databases, RAG, 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 production workloads.
- Experience with Snowpark and Snowflake Cortex capabilities (Cortex AI, Cortex Search, Cortex Agents, external stages, streams/tasks, dynamic tables) is highly desirable.
- Hands-on experience integrating data and AI solutions with Microsoft Azure, especially 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, CI/CD, automated testing, environment management, code review, and controlled production deployment.
- Ability to assess business problems and determine when AI is the right fit.
- Strong analytical, problem-solving, and communication skills, with independence and effective cross-team collaboration.
- Experience working with sensitive or highly regulated data is strongly preferred, including banking, financial services, fintech, or similar regulated industries.
- Leads with accountability, integrity, consistency; supports transparency and follow-through; maintains professionalism and composure under pressure.
- Embraces data-driven decision-making with a client-first perspective.
Technologies
- 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
- Los Angeles, Orange County, San Diego
Responsible AI & Banking Environment
Because AI in financial services must be implemented thoughtfully, the Senior AI Engineer is expected to approach development with strong understanding of data privacy, cybersecurity, model risk, third-party risk, explainability, access controls, human oversight, and regulatory compliance. The goal is to build sustainable capabilities that employees and leadership can trust and that support the Bank’s long-term strategy.
AML/CFT/Compliance Responsibilities
- This role includes direct or indirect interaction with customers and other employees and includes responsibilities related to BSA/AML.
- The employee may examine and view information and documents produced by others relating to BSA and therefore 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 escalating suspicious activity to the BSA Officer.
Physical Demands
- May require some travel to support team, department, and initiatives.
- Ability to sit or stand for extended periods of time.
- Ability to use a keyboard and mouse.
- Ability to 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 include close vision and ability to adjust focus.
