Principal Engineer

Responsibilities

• Own the strategic direction and modernization of enterprise data platforms and data architectures.
• Design and govern batch processing, streaming pipelines, real-time event processing, lakehouse, data mesh, and domain-oriented data product solutions.
• Lead architecture decisions and standards for data quality, lineage, metadata, observability, governance, security, and compliance.
• Provide technical leadership for enterprise application platforms, Java and Spring Boot microservices, REST APIs, event-driven architectures, and distributed systems.
• Define engineering standards for secure coding, API design, test automation, observability, documentation, scalability, availability, performance, and operability.
• Lead enterprise adoption of generative AI, including RAG pipelines, agentic AI, multi-agent orchestration, and LLM-powered business applications.
• Design AI architecture and governance standards covering responsible AI, model observability, security, compliance, and evaluation frameworks.
• Lead role-based autonomous agent implementations and partner with data science and ML teams to operationalize AI solutions at scale.
• Set cloud and platform strategy across Azure and GCP, using Docker, Kubernetes, infrastructure as code, and cloud-native services.
• Optimize reliability, scalability, performance, operational cost, resiliency, and disaster recovery for mission-critical platforms.
• Align engineering roadmaps with enterprise strategy, evaluate emerging technologies and build-versus-buy decisions, and influence senior leadership and technology investments.
• Partner with product management, architecture, data science, infrastructure, security, platform engineering, and business stakeholders.
• Mentor senior engineers and lead effectively across ambiguity, regulatory focus, and high-visibility initiatives.

Requirements

• 7+ years of engineering experience or equivalent demonstrated through work experience, training, military experience, or education.
• 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.
• Deep expertise in data engineering, Java/Spring Boot microservices, and generative AI.
• Experience building mission-critical platforms for 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 legacy-to-cloud modernization programs.
• Proven ability to influence CIO, CTO, senior executive, business, and risk stakeholders.
• Experience with Spark, PySpark, Kafka, Flink, Snowflake, Databricks, Iceberg, Delta Lake, data lake/lakehouse architectures, real-time streaming platforms, data governance, and lineage.
• Experience with Java, Spring Boot, microservices, REST APIs, event-driven architectures, and distributed systems.
• Experience with LLMs, RAG architectures, vector databases, prompt engineering, agentic AI, and multi-agent orchestration.
• Experience with one or more of LangChain, LangGraph, Google ADK, CrewAI, or AutoGen.
• Programming experience with Python and Java.
• Experience with Azure or GCP, Docker, Kubernetes, CI/CD platforms, and infrastructure as code.
• Ability to explain complex technical and data concepts to senior business and risk leaders and lead in a large, matrixed organization.
• Strong risk-aware mindset and high standards for engineering discipline, documentation, operational stability, compliance, and sound risk decisions.

Benefits

• The posting identifies Wells Fargo as an equal opportunity employer and provides disability accommodations upon request.
• The role supports a risk-mitigating, compliance-driven culture with emphasis on governance, monitoring, escalation, and regulatory obligations.
• Posting end date is September 30, 2026, although the posting may close earlier due to applicant volume.