Principal Engineer – Data Engineering, AI & Distributed Systems

About this role:

Wells Fargo is seeking a highly experienced Principal Engineer to provide technical leadership across enterprise data platforms distributed systems AI solutions and cloud-native application architectures. This role will drive the strategic direction for data engineering real-time analytics AI-enabled solutions and microservices platforms that power critical business capabilities at global scale.

In this role you will:

• Act as an advisor to leadership to develop or influence applications network information security database operating systems or web technologies for highly complex business and technical needs across multiple groups
• Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise delivering solutions that are long-term large-scale and require vision creativity innovation advanced analytical and inductive thinking
• Translate advanced technology experience an in-depth knowledge of the organizations tactical and strategic business objectives the enterprise technological environment the organization structure and strategic technological opportunities and requirements into technical engineering solutions
• Provide vision direction and expertise to leadership on implementing innovative and significant business solutions
• Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
• Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership

Required Qualifications:

• 7 years of Engineering experience or equivalent demonstrated through one or a combination of the following: work experience training military experience education

Desired Qualifications:

• The ideal candidate is a recognized technical leader with deep expertise in Data Engineering Java/Spring Boot Microservices and Generative AI capable of influencing architecture decisions mentoring senior engineers and shaping long-term technology role requires balancing innovation with operational excellence ensuring platforms are secure scalable resilient cost-efficient and aligned with business outcomes.
• 7 years of software engineering experience with significant leadership responsibilities.
• 7 years designing and delivering large-scale data engineering solutions.
• 7 years leading cloud-native architectures.
• 3 years of hands-on Generative AI implementation experience.
• Experience building mission-critical platforms supporting finance treasury risk or regulatory functions.
• Experience training fine-tuning and deploying LLMs in enterprise environments.
• Experience implementing enterprise-wide AI governance and responsible AI frameworks.
• Experience leading large modernization programs involving legacy-to-cloud migration.
• Proven track record influencing CIO CTO and senior executive stakeholders.

Data Engineering Leadership

Own the strategic direction and modernization of enterprise data platforms.

Responsibilities

• Design and evolve scalable data architectures including:
  • Batch processing
  • Streaming pipelines
  • Real-time event processing
  • Lakehouse architectures
  • Data Mesh and Domain-Oriented Data Products
• Lead architectural decisions involving:
  • Apache Spark
  • Kafka
  • Iceberg / Delta Lake
  • Snowflake
  • Databricks
  • Flink
  • Cloud-native data platforms
• Define standards for:
  • Data quality
  • Data lineage
  • Metadata management
  • Observability
  • Governance
  • Data Security and Compliance
• Drive modernization initiatives from legacy data platforms toward scalable cloud-native architectures.

Software Engineering Leadership

Provide technical leadership across enterprise application platforms and distributed systems.

Responsibilities

• Design and govern enterprise software architecture using:
  • Java
  • Spring Boot
  • REST APIs
  • Event-Driven Architectures
  • Kafka
  • Distributed Systems Patterns
• Define standards for:
  • Secure coding
  • API design
  • CI/CD
  • Test automation
  • Observability
  • Documentation
• Lead architecture reviews and ensure solutions meet:
  • Scalability targets
  • Availability requirements
  • Security standards
  • Performance SLAs
  • Operability objectives
• Drive adoption of cloud-native engineering practices and modern software delivery models.

AI & Generative AI Leadership

Lead enterprise adoption of AI and GenAI technologies to transform business processes and engineering productivity.

Responsibilities

• Architect and deliver enterprise-scale GenAI solutions leveraging:
  • Retrieval-Augmented Generation (RAG)
  • Agentic AI frameworks
  • Multi-Agent Orchestration
  • LLM-powered business applications
• Design end-to-end RAG pipelines including:
  • Document ingestion
  • Chunking strategies
  • Embedding generation
  • Vector databases
  • Retrieval optimization
  • Context augmentation
  • Response orchestration
• Define enterprise AI architecture and governance standards covering:
  • Responsible AI
  • Model observability
  • Security
  • Compliance
  • Evaluation frameworks
• Lead implementation of role-based autonomous agent systems using frameworks such as:
  • LangChain
  • LangGraph
  • CrewAI
  • AutoGen
  • Google ADK
• Partner with Data Science and ML teams to operationalize AI solutions at scale.

Cloud & Platform Engineering

Responsibilities

• Lead cloud strategy and architecture across:
  • Azure
  • GCP
• Design scalable platform solutions using:
  • Docker
  • Kubernetes
  • Infrastructure as Code
  • Cloud-native services
• Optimize cloud reliability scalability performance and operational cost.
• Establish resiliency and disaster recovery standards for mission-critical platforms.

Strategic Influence

Responsibilities

• Align engineering roadmaps with enterprise business and technology strategy.
• Shape long-term architecture direction across data AI and application platforms.
• Evaluate emerging technologies and industry trends including:
  • Generative AI
  • Agentic AI
  • Data Mesh
  • Real-Time Analytics
  • Autonomous Engineering Platforms
• Influence senior leadership and stakeholders on strategic technology investments.
• Evaluate build-versus-buy decisions vendor solutions and platform partnerships.

Cross-Functional Collaboration

Responsibilities

• Partner with:
  • Product Management
  • Architecture
  • Data Science
  • Infrastructure Engineering
  • Security Engineering
  • Platform Engineering
  • Business Stakeholders
• Drive alignment between business objectives and technical execution.
• Enable access to trusted reliable and governed enterprise data assets.

Technical Skills

• Data Engineering:
  • Spark PySpark Kafka Flink Snowflake Databricks Iceberg Delta Lake
  • Data Lake/Lakehouse architectures
  • Real-Time Streaming Platforms
  • Data Governance and Lineage
• Software Engineering
  • Java Spring Boot Microservices REST APIs
  • Event-Driven Architectures
  • Distributed Systems
• AI / GenAI
  • understanding of LLMs
  • RAG Architectures
  • Vector Databases
  • Prompt Engineering
  • Agentic AI
  • Multi-Agent Orchestration
• Experience with one or more:
  • LangChain
  • LangGraph
  • Google ADK
• Programming
  • Python Java
• Cloud & DevOps
  • Azure / GCP
  • Docker
  • Kubernetes
  • CI/CD platforms
  • Infrastructure as Code

Job Expectations:

• Strong riskaware mindset aligned with Wells Fargos culture and values
• Ability to explain complex technical and data concepts to senior business and risk leaders
• Proven ability to influence and lead in a large matrixed organization
• High standards for engineering discipline documentation and operational stability
• Effective leadership during ambiguity regulatory focus or highvisibility initiatives
• Be Humble: Youre smart yet always interested in learning from others.
• Work Transparently: You always deal in an honest direct and transparent way.
• Take Ownership: You embrace responsibility and find joy in having the answers.
• Learn More: You regularly self-educate and improve your skill set.
• Show Gratitude: You show appreciation and respect to those you work with.
  

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 units risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates including women persons with disabilities aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

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

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