Job Summary

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 recent 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

📌 Principal Engineer Data Engineering, AI & Distributed Systems (Bengaluru)
🏢 Wells Fargo
📍 Bengaluru