AI & Data Systems Engineer

CAIS is the pioneer in democratizing access to and education about alternative investments for independent financial advisors, empowering them to engage and transact with leading asset managers on a massive scale through a wide variety of alternative investment products and technology solutions. CAIS provides financial advisors with a broad selection of alternative investment strategies, including hedge funds, private equity, private credit, real estate, digital assets, and structured notes. CAIS also delivers industry-leading technology, operational efficiency, and world-class client service throughout the pre-trade, trade, and post-trade experience. CAIS supports over 50,000 advisors who oversee more than $6 trillion in network assets.   

CAIS is transforming Platform Operations from a primarily manual function into a technology-enabled business transformation organization. The AI & Data Systems Engineer joins the Business Transformation (BT) team as its technical backbone — configuring, integrating, and deploying solutions rapidly without building software from scratch.

The BT team partners with the AI & Data Technology teams to optimize solutions & deployment processes on platforms including Snowflake (Cortex, Streamlit), N8N, Airtable, Salesforce, DataHub, Claude/CoWork, and Stonly. You will unblock the team, accelerate automation delivery, and help establish the guardrails needed to scale safely — in close partnership with the Technology organization. 

Responsibilities

Platform & Integration 

• Own configuration and integration of BT's tool stack; resolve API, connectivity, and configuration blockers 
• Design and implement Salesforce ↔ Snowflake integrations and other cross-system data flows 
• Build Streamlit apps and operational dashboards that put data directly in business users' hands 

AI & Automation Enablement 

• Deploy intelligent automations using Snowflake Cortex, Claude/CoWork, N8N, and AI-native tooling 
• Co-pilot BT team members through prototyping, testing, and operationalizing agentic workflows 
• Create reusable templates and automation patterns that raise the team's overall delivery velocity 

Data & Reporting Operations 

• Maintain Snowflake queries, data models, and reporting layers serving BT's operational and analytical needs 
• Use DataHub to catalog assets and support data discoverability across the BT environment 
• Assist in ensuring data security and integrity in partnership with Engineering and InfoSec teams 

Engineering Practices & Safe Delivery 

• Partner with Technology to implement SDLC, testing, deployment, and version control practices for BT's tool stack 
• Define lightweight automation standards (reliability, error handling, logging) — guardrails that enable speed, not