Principal Engineer - Public Cloud Data

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.
$159,000.00 - $254,000.00
Benefits
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.
Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement
Posting End Date:
8 Sep 2026
*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 Wel