BENGALURU · FULLTIME
Principal Engineer Data Engineering, AI & Distributed Systems
Wells Fargo
Bengaluru · onsite · Posted 27d ago
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Undisclosed7–12 yrsfulltimeBengaluru
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Section · 01
About this role
Job Summary
In this role, you will
Required Qualifications
Desired Qualifications
Data Engineering Leadership
Responsibilities
Software Engineering Leadership
Responsibilities
AI Generative AI Leadership
Responsibilities
Cloud Platform Engineering
Responsibilities
Strategic Influence
Responsibilities
Cross-Functional Collaboration
Responsibilities
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 strategy. This 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
- Distributed Systems Patterns
- Define standards for:
- Secure coding
- API design
- CI/CD
- Test automation
- 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
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Section · 02
Skills
AutomationApache SparkBatch processingApplication ArchitecturesCrewaiapisApacheapi designai frameworksCloud Strategyai governanceAnalyticscloudCloud MigrationArchitecturecomplianceAi SolutionsMicrosoft AzureArtificial Intelligence
Section · Company
About Wells Fargo
Wells Fargo
Financial Services
20k+
employees
1852
174 years old
Bengaluru/Bangalore, Karnataka
India
About
Wells Fargo works to create positive social impact in the communities it serves by supporting housing affordability, small business growth, financial health, and a low-carbon economy.
Industries
Financial Services
Employee ratings
8,681 reviews
3.6/ 5
Culture
3.5
Career growth
2.9
Work-life
3.8
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