About this role:

• The Principal Engineer for Public Cloud Data, Analytics & Agentic AI Platform is the senior-most technical leader responsible for defining and driving the strategic architecture, engineering standards, and innovation roadmap for enterprise-scale data, analytics, and Agentic AI capabilities on public cloud platforms.

• This role serves as the technical authority for modern data platforms, AI-native architectures, and autonomous agent solutions that enable self-service analytics, intelligent automation, real-time decisioning, and enterprise-scale data products. The Principal Engineer partners with engineering, architecture, cybersecurity, risk, compliance, product, and business leaders to accelerate cloud transformation while maintaining security, governance, resilience, and regulatory compliance.

In this role, you will:

• Define the target-state architecture for cloud-native data, analytics, AI/ML, and Agentic AI platforms
• Establish engineering standards, reference architectures, reusable patterns, and technical governance across the enterprise
• Drive modernization of legacy data platforms into scalable cloud-native ecosystems
• Lead technology evaluations and strategic adoption of emerging public cloud capabilities
• Architect and scale enterprise lakehouse, data mesh, streaming, and real-time analytics platforms
• Define standards for data ingestion, transformation, governance, metadata management, lineage, and data quality
• Enable self-service data products and analytics capabilities across business lines
• Lead the development of Agentic AI solutions that automate engineering, operations, governance, and analytics workflows
• Define enterprise frameworks for AI agents, orchestration, reasoning engines, MCP-based integrations, and human-in-the-loop controls
• Architect AI-enabled automation for:
  • Data onboarding
  • Pipeline generation
  • Metadata enrichment
  • Policy enforcement
  • Data quality validation
  • Incident remediation
  • Operational intelligence
• Establish standards for responsible AI, explainability, model governance, and auditability
• Provide technical leadership across public cloud services including compute, storage, networking, security, AI, analytics, and DevOps ecosystems
• Drive platform reliability, scalability, resiliency, observability, disaster recovery, and operational excellence
• Partner with engineering teams to implement Infrastructure as Code (IaC), platform automation, and self-service capabilities
• Establish SLOs, reliability metrics, and engineering KPIs
• Partner with Cyber Security, IAM, Risk, Audit, and Regulatory Compliance teams
• Ensure cloud platforms meet enterprise security, governance, privacy, and regulatory standards
• Architect secure-by-design and compliance-by-design platform capabilities
• Drive implementation of AI governance controls for enterprise-scale Agentic AI adoptio
• Design high-performance, secure, and cost-efficient cloud data ecosystems supporting regulatory and business requirements

Required Qualifications:

• 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• 7+ years designing enterprise-scale data and analytics platforms
• 5+ years delivering AI/ML, Generative AI, or Agentic AI solutions in complex enterprise environments
• Proven experience leading enterprise-wide cloud transformation initiatives

Desired Qualifications:

• Deep expertise in one or more public cloud platforms:
  • Google Cloud Platform (preferred)
  • Microsoft Azure
  • Amazon Web Services
• Strong experience with:
  • Data Lakehouse architectures
  • BigQuery, Snowflake, Databricks, Starburst, or equivalent platforms
  • Streaming and event-driven architectures
  • Data governance, metadata, lineage, and catalog solutions
  • Kubernetes and container platforms
  • Infrastructure as Code and DevOps automation

• AI & Agentic AI Expertise

• Experience designing enterprise AI platforms and MLOps frameworks.
• Large Language Models (LLMs)
• Retrieval Augmented Generation (RAG)
• Agentic AI architectures
• Multi-agent systems
• Vector databases
• Model evaluation and monitoring
• MCP (Model Context Protocol) ecosystems
• Experience implementing production-grade AI governance and controls
• Advanced degree in Computer Science, Engineering, Data Science, AI, or related field
• Industry certifications in public cloud, data engineering, AI/ML, or security.
• Experience in highly regulated industries such as financial services, healthcare, or insurance
• Contributions to industry standards, patents, open-source projects, or published technical thought leadership

Job Expectations:

• This position is not eligible for visa sponsorship
• Telecommuting is not an option for this position
• This position offers a hybrid work schedule
• Relocation assistance in not available for this position

Pay Range
 

Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities.

Posting End Date:

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace.  Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.