Generative AI Enterprise Architect

Our vision for the future is based on the idea that transforming financial lives starts by giving our people the freedom to transform their own. We have a flexible work environment, and fluid career paths. We not only encourage but celebrate internal mobility. We also recognize the importance of purpose, well-being, and work-life balance. Within Empower and our communities, we work hard to create a welcoming and inclusive environment, and our associates dedicate thousands of hours to volunteering for causes that matter most to them.

Chart your own path and grow your career while helping more customers achieve financial freedom. Empower Yourself.

***Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time, including CPT/OPT.***

The Generative AI – Enterprise Architect owns the architectural strategy and key decisions for how Generative AI capabilities are built, scaled, and integrated across the enterprise. This role defines how enterprise data and knowledge are structured, accessed, and applied to support AI-driven interactions across customer experiences, internal workflows, and decision-making processes.

This role is accountable for how information flows from source systems through curation, indexing, and retrieval into AI-enabled systems. It establishes the patterns, constraints, and standards that govern how AI operates within the enterprise, and ensures those patterns are applied consistently through close partnership with engineering and platform teams.

This role continuously evolves the architecture based on real-world system behavior, adoption patterns, and emerging capabilities, ensuring Generative AI becomes a reliable, scalable, and integral part of how the organization operates.

What You Will Do

• Own the architectural strategy and key decisions for how Generative AI capabilities are designed and scaled across the enterprise

• Define how enterprise data, knowledge, and metadata are organized so AI systems can reliably access and use them

• Establish how information flows from source systems through curation, indexing, embedding, and retrieval into AI-driven interactions

• Set direction for how AI capabilities are embedded into customer touchpoints, internal tools, and operational workflows

• Develop Agent Framework Architecture

• Define how enterprise data models and domain structures enable contextual reasoning and grounded outputs

• Establish how knowledge is represented, versioned, and maintained to ensure accuracy and relevance over time

• Define how retrieval systems select, rank, and deliver context to models under varying conditions

• Establish patterns for handling non-deterministic system behavior, including variability, ambiguity, and failure scenarios

• Define how orchestration layers coordinate models, data sources, APIs, and downstream systems into controlled workflows

• Establish patterns for multi-step AI workflows, including tool usage, execution boundaries, and escalation paths

• Assist the RAI team with defining how AI outputs are evaluated for quality, consistency, and impact on downstream decisions and processes

• Identify fragmentation across data, tools, and implementations and drive consolidation into coherent architectural patterns

What You Will Bring

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

• Ten or more years of experience across data architecture, distributed systems, or enterprise platform design

• Experience owning architectural direction and influencing system design across multiple teams

• Strong understanding of data architecture, including how structured and unstructured data is modeled, governed, and made accessible across complex systems

• Experience designing large-scale systems that integrate data platforms, APIs, and distributed services

• Practical knowledge of modern data platforms (such as snowflake) including ingestion, transformation, and consumption layers

• Understanding of retrieval, indexing, and search systems operating at scale

• Deep familiarity with Generative AI and Agentic AI concepts including embeddings, retrieval, prompt composition, agent memory, and orchestration

• Ability to design systems that balance performance, scalability, cost, and operational complexity

• Strong grasp of access control, security, and governance within distributed environments

• Expe…