Generative AI Enterprise Architect

Empower

1d • $151,800 - $220,050 • Hybrid

About The Position

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. We are looking for an Enterprise Data Architect to own how Generative AI capabilities are designed, structured, and scaled across the enterprise. This role defines how data, knowledge, and large language models (LLM) come together to power AI-driven interactions across customer experiences, internal tools, and business workflows. You will shape how information flows across the organization and how AI systems access, interpret, and apply that information. This includes defining how structured data and unstructured knowledge are prepared, indexed, and retrieved to support reliable, high-quality outputs. This is a strategic architecture role with direct influence on how systems are built. You will set architectural direction, make key design decisions, and guide engineering and platform teams to ensure a consistent and scalable approach.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
• 10+ years of experience in data architecture, AI/ML systems, or distributed platform design
• Experience setting architectural direction and influencing system design across teams
• Strong background in data modeling, data pipelines, and large-scale data systems
• Understanding of retrieval, search, and indexing systems, along with Generative AI architectures including LLMs, embeddings, RAG, tool-calling agents, API integration, human-in-the-loop approvals, agent identity, multi-agent patterns, MCP and A2A-style integrations, and controlled autonomy
• Experience with modern data and cloud platforms, especially AWS and Snowflake, including Bedrock, vector databases, hybrid search, APIs, event-driven architecture, IAM, observability, CI/CD, infrastructure as code, and model selection across LLMs, SLMs, and multimodal models
• Ability to design systems that balance scalability, performance, cost, and operational complexity

Nice To Haves

• Experience architecting or scaling Generative AI or LLM-based systems in production environments
• Depth in information retrieval, semantic search, or knowledge-based architectures
• Experience designing systems where AI outputs directly influence user decisions, workflows, or downstream actions
• Strong intuition for how data structure, context selection, and retrieval design impact AI output quality and reliability
• Practical understanding of system failure modes and how to design safeguards for non-deterministic behavior
• Recognized expertise through targeted certifications in AWS, Snowflake, or applied machine learning, with exposure to Generative AI platforms such as AWS Bedrock or similar

Responsibilities

• Define the architectural strategy for Generative AI, LLM, and AI platform capabilities across the enterprise
• Shape how enterprise data, knowledge, and metadata are structured and accessed for AI-driven use cases
• Establish patterns for how data flows across ingestion, transformation, indexing, embeddings, and retrieval
• Guide how AI systems handle ambiguity, variability, and non-deterministic behavior
• Influence how models, data sources, APIs, and workflows are orchestrated into scalable systems
• Establish how AI systems are evaluated, observed, and operated in production, including output quality, system behavior, and reliability

Benefits

• Medical, dental, vision and life insurance
• Retirement savings – 401(k) plan with generous company matching contributions (up to 6%), financial advisory services, potential company discretionary contribution, and a broad investment lineup
• Tuition reimbursement up to $5,250/year
• Business-casual environment that includes the option to wear jeans
• Generous paid time off upon hire – including a paid time off program plus ten paid company holidays and three floating holidays each calendar year
• Paid volunteer time — 16 hours per calendar year
• Leave of absence programs – including paid parental leave, paid short- and long-term disability, and Family and Medical Leave (FMLA)
• Business Resource Groups (BRGs) – BRGs facilitate inclusion and collaboration across our business internally and throughout the communities where we live, work and play. BRGs are open to all.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior