AI Ecosystem and Integration Specialist

Diversify•South Jordan, UT

About The Position

The AI Ecosystem and Integration Specialist is a senior technical leader responsible for understanding how Diversify’s data, platforms, and workflows connect and ensuring they are integrated effectively enough for AI to operate across them. The role partners with business stakeholders, platform owners, and engineering teams to define the target AI architecture and determine what needs to be addressed before agents can perform useful work. It combines strategic architecture with hands-on integration work as needed. The position also requires continuous learning about emerging AI capabilities and their implications for wealth management, translating that knowledge into improved solutions for the firm, its advisors, and its clients. The specialist maps systems, data sources, and flows; identifies and resolves integration, data-quality, and ownership gaps; and evaluates AI developments, vendor approaches, standards, security practices, and regulatory guidance. The role establishes secure connections between advisor-facing platforms and required systems, defines standards for access, security, and governance, and advises leadership on options, risks, tradeoffs, and use-case priorities.

Requirements

At least 6 years of experience in solutions architecture, data or integration engineering, or technical strategy.
At least the last 2 years focused on AI integration and architecture directly related to this position.
Strong systems-thinking skills and the ability to balance immediate delivery needs with long-term scalability.
Demonstrated ability to influence across departments without formal authority.
Clear communication skills, including the ability to explain technical concepts to non-technical audiences.
A habit of continuous learning and staying current in a rapidly changing field.
Solution-focused, flexible, and user-centric approach.
Deep understanding of system integrations, data models, and security considerations.
Strong Python and JavaScript/TypeScript skills.
Working knowledge of data architecture, data lakes, data management, Postgres, graph databases, and how agent-built software relies on them.
Hands-on experience with APIs, integration platforms or ETL tools, and cloud environments.
Ability to rapidly assess gaps and recommend practical solutions.

Nice To Haves

Familiarity with the wealth management technology landscape, or the curiosity to learn it quickly.
Hands-on LLM and agent experience, and familiarity with MCP or similar integration patterns.
Experience working in a highly regulated industry.

Responsibilities

Inventory systems, data sources, and data flows, and document how they relate.
Identify integration gaps, data-quality problems, and ownership issues, and lead efforts to address them.
Track AI advancements relevant to wealth management, including models, integration standards, data and security practices, peer and vendor adoption, and regulatory guidance.
Assess emerging options within the company’s ecosystem, recommend build, buy, or partner decisions, and regularly brief leadership on their architectural and roadmap implications.
Ensure the advisor-facing platform is securely connected to needed data and systems, with access controls and activity logging that support oversight.
Define the company-wide target architecture for AI, including safe ways for agents to access data and tools.
Establish access, security, and governance standards and documentation that support long-term scalability.
Advise leaders on options, risks, and tradeoffs, and help prioritize use cases by value and feasibility.
Partner with business stakeholders, platform owners, and engineering teams to shape architecture and carry out integration work as needed.