Principal Enterprise Data & AI Architect

100 Raymond James & Associates, Inc.; Saint Petersburg (FL); Hybrid; USD 180,000 - 280,000; Full time

Benefits offered by this job

Medical, dental, and vision

Life insurance

Disability benefits

Retirement savings

Paid time off

Parental leave

Job summary

Raymond James seeks a Principal Enterprise Data & AI Architect to define and operationalize architecture across enterprise data platforms and AI/ML capabilities. The role requires hands-on credibility in cloud-based data platforms, governance, and scalable reference frameworks. The hybrid schedule includes 2–3 in-office days weekly at our St.

Petersburg, FL Corporate Office. The ideal candidate will lead target-state architectures, modern data lakehouse and AI patterns, and governance controls

Qualifications

• 15+ years of experience in data architecture, enterprise architecture, cloud data architecture, data engineering architecture, AI architecture, ML architecture or related senior technology roles.
• Deep expertise in enterprise data architecture including data engineering, data lakehouse, data products, metadata, lineage, data quality, semantic layers and governed data access.
• Experience with analytical/AI cloud platforms like AWS Redshift, Snowflake, Databricks, BigQuery.
• Experience with cloud data platforms such as Aurora, Postgres, DynamoDB and graph databases like Neo4j, Neptune.
• Strong AI/ML platform engineering and architecture experience with AWS Sagemaker, AWS Bedrock, vector stores and ML Ops/LLM Ops.

Responsibilities

• Serve as principal enterprise architect for data platforms and AI/ML capabilities, define architecture strategy and reference designs.
• Define target-state architecture for modern cloud data and AI platforms including data stores, lakehouses, semantic layers, APIs, and governed data access.
• Lead data platform modernization, evaluate legacy vs. modern capabilities, and guide migrations to scalable cloud platforms.
• Evaluate cloud technologies using criteria for scalability, security, performance, cost, and enterprise fit.
• Design scalable patterns for data ingestion, transformation, storage, and consumption across batch, streaming, real-time, analytics and ML use cases.
• Evolve agentic data-access architecture to production-grade implementation with secure, auditable adapters.
• Drive architecture reviews, identify risks, gaps, and opportunities for reuse, with focus on non-functional requirements.
• Translate business and data needs into practical roadmaps, patterns, and migration plans.
• Partner with EA, AI execution teams, data engineering/science, security, governance, and business stakeholders.
• Mentor engineers and delivery teams on patterns, AI/data design, and production-grade delivery.

Skills

Enterprise data architecture

Cloud data architecture

AI architecture

ML architecture

Data governance

Stakeholder influence

Architectural patterns

Education

Bachelor’s: Computer and Information Science

Bachelor’s: Computer Engineering

Tools

AWS Redshift

Snowflake

Databricks

Google BigQuery

Aurora

Postgres

DynamoDB

Neo4j

Neptune

SageMaker

Bedrock

OpenSearch

ML Ops

LLM Ops

Job description

Job Description Summary

We are seeking a highly experienced Principal Enterprise Data & AI Architect to define, evolve, and operationalize architecture across enterprise data platforms and AI/ML platform capabilities. The candidate must be a very strong Data & AI architect with deep hands-on engineering credibility in cloud-based data platforms, enterprise-scale AI architecture, and production-grade reference frameworks and solution design. The Architect will advance governed agentic data-access architecture from reference design to working production-grade solutions. The architect will establish reusable agent design patterns, Data/AI reference architectures, and engineering frameworks that enable delivery teams and business teams to adopt AI capabilities safely, consistently, and at scale. The successful candidate will connect trusted enterprise data with scalable AI execution. They will define how data platforms, semantic models, ontologies, knowledge graphs, AI agents, governance controls, and engineering standards work together to support analytics, advanced analytics, AI-enabled business workflows, and self-service data access.

Job Description This position follows our hybrid-friendly schedule, so you get the best of both worlds – flexibility and collaboration. In office days will be 2-3 per week averaging 10-12 days per month in our St Petersburg, FL Corporate Office.

Key Responsibilities and Essential Duties

Serve as the principal enterprise architect for enterprise data platforms and AI/ML platforms/capabilities, agentic data access, semantic enablement, and data engineering standards. Own the architecture strategy, target-state designs, reference architectures, implementation blueprints, technical guardrails, and engineering standards for trusted, governed, scalable data and AI capabilities.

Define target-state architecture for modern cloud-based data and AI platforms, including operational data stores, cloud data warehouses, data lakehouses, data products, semantic layers, AI/ML platforms, vector stores, APIs, agentic data access services, and governed data consumption capabilities.

Lead core data platform modernization by evaluating legacy and modern platform capabilities, defining workload placement criteria, and guiding migration from on-premises data platforms to scalable, governed, AI-ready cloud platforms.

Evaluate and recommend cloud data, analytics, AI, semantic, governance, and engineering technologies using decision criteria based on scalability, security, interoperability, performance, resilience, cost, supportability, and enterprise fit.

Design scalable architecture patterns for data ingestion, transformation, storage, curation, publishing, retrieval, and consumption across batch, streaming, event-driven, real-time, analytics, machine learning, generative AI, and agentic use cases.

Define architecture patterns for machine learning, generative AI, AI services, intelligent applications, AI-enabled analytics, retrieval-augmented generation, workflow automation, and agentic AI solutions.

Evolve governed agentic data-access architecture from reference design to production-grade implementation, including agent-safe tools and API adapters that are read-optimized, entitled, audited, secure, and appropriate for regulated enterprise use.

Drive architecture reviews for data and AI initiatives, identifying design risks, integration gaps, scalability concerns, governance needs, operational readiness issues, supportability gaps, and opportunities for reuse.

Define non-functional requirements for data and AI solutions, including scalability, performance, latency, availability, resilience, observability, maintainability, cost efficiency, and operational supportability.

Translate complex business, data, and AI requirements into practical architecture roadmaps, implementation patterns, reusable engineering frameworks, and migration plans.

Partner closely with Enterprise Architecture, Enterprise Data & Analytics, AI execution teams, data engineering, data science, analytics, cloud/platform engineering, application teams, security, risk, compliance, governance, and business stakeholders.

Mentor engineers, architects, and delivery teams on architecture patterns, AI/data design practices, engineering standards, operational readiness, and production-grade solution delivery.

Required Qualifications

15+ years of experience in data architecture, enterprise architecture, cloud data architecture, data engineering architecture, AI architecture, ML architecture, or related senior technology roles.

Deep expertise in enterprise data architecture, including data engineering, data lakehouse architecture, data lakes, data products, metadata, lineage, data quality, semantic layers, and governed data access.

Strong engineering and architecture experience with analytical/AI cloud-based data platforms such as AWS Redshift, Snowflake, Databricks, Google BigQuery or comparable technologies.

Strong engineering and architecture experience with operational cloud-based data platforms such as Aurora, Postgres, Dynamo DB and Graph data platforms such as Neo4J, Neptune and related technologies.

Strong AI/ML platform engineering and architecture experience with AWS Sagemaker, AWS Bedrock, Vector databases like Open Search, ML Ops and LLM Ops.

Experience defining agent design patterns, AI/data reference architectures, reusable frameworks, technical guardrails, engineering standards, and production-ready architecture patterns.

Deep expertise in agentic AI and LLM application architecture, including cloud-native AI/ML platform integration, model selection, prompt engineering, retrieval-augmented generation, tool/API integration, context and memory management, orchestration patterns, and production-grade frameworks for building scalable AI solutions.

Familiarity with MCP-based tooling, Agent Harness or equivalent technologies is preferred.

Strong understanding of data governance, AI governance, privacy, security, access controls, auditability, regulatory expectations, model risk, and operational risk in enterprise environments.

Experience designing AI-ready data architectures that support analytics, machine learning, generative AI, enterprise search, intelligent applications, AI agents, and operational AI use cases.

Ability to influence senior stakeholders and explain complex data and AI architecture concepts clearly to technical and non-technical audiences.

Experience in wealth management, financial services, brokerage, asset management industries.

Ideal Candidate Profile

The ideal candidate is a deeply technical Principal Data & AI Architect who can lead architecture across enterprise data platforms, AI/ML solutions, agentic data access, semantic and AI context architecture. This person should be strong enough in data architecture to design the trusted cloud data foundation required for analytics and AI, and strong enough in AI architecture to guide how AI agents, machine learning, generative AI, retrieval systems, and intelligent applications are integrated, governed, deployed, monitored, and scaled. This is not a generalist architect role. It requires strong data engineering/architecture depth, practical AI/ML architecture experience, cloud platform expertise, production engineering discipline, and the ability to influence across data, AI, cloud, engineering, security, governance, risk, compliance, and business teams.

Education

Bachelor’s: Computer and Information Science (Required), Bachelor’s: Computer Engineering

Work Experience

General Experience – 10 to 15 years

Travel

Less than 25%

Workstyle

Hybrid

The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions.

• medical, dental, and vision
• life insurance
• critical illness insurance and accident insurance
• disability benefits
• retirement savings
• paid time off (including vacation, holidays, and sick leave)
• parental leave

Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.

At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view.

We expect our associates at all levels to:

• Grow professionally and inspire others to do the same
• Work with and through others to achieve desired outcomes
• Make prompt, pragmatic choices and act with the client in mind
• Take ownership and hold themselves and others accountable for delivering results that matter
• Contribute to the continuous evolution of the firm

At Raymond James – as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates. When associates bring their best authentic selves, our organization, clients, and communities thrive.

The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.

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Raymond James is a diversified financial services company providing wealth management, capital markets, asset management, banking and other services to individuals, corporations and municipalities. Founded in 1962 in St. Petersburg, Florida, rather than on Wall Street, we have always embraced being a different kind of financial services firm.

Today, Raymond James has locations and subsidiaries across the United States, Canada, the United Kingdom and Germany, and is listed on the New York Stock Exchange under the symbol RJF.

Thanks for your interest in working with Raymond James. While we might not have the perfect role for you today, we'd love to keep in touch. Our business is deeply focused on people and their financial well-being. We're committed to helping individuals, corporations and institutions achieve their goals, while also supporting successful professionals and helping our communities prosper. We believe doing well and doing good aren't mutually exclusive. As an established but ever-evolving company, you can start – or continue – growing your career here. We invest in you with wide-ranging benefits and the support of leaders and colleagues who care. From development opportunities and enriching networking groups to prioritizing diversity, inclusion and the power of different perspectives, Raymond James is where good people grow. Our people-first culture is outlined in our Culture Blueprint. Check it out to see why many choose to work at Raymond James – and why they stay.