Principal Engineer - IDOCS Gen AI Solution Lead

Wells Fargo & Company•Charlotte, NC

2d•Hybrid

About The Position

Wells Fargo is seeking a Principal Engineer for the Digital Technology & Innovation team, specifically within Enterprise Content Management (ECM), focusing on Intelligent Document Services (IDOCS). IDOCS is described as one of the most robust, mission-critical, high-scale production platforms in the enterprise, managing over 50 billion documents and acting as a trusted AI system. This role requires a hands-on technologist with deep Java ecosystem expertise to architect, design, develop, and scale enterprise-grade AI systems, operating at a global banking scale within a highly regulated financial environment. The Principal Engineer for IDOCS will lead the architecture and design of next-generation AI solutions, transforming document operations such as classification, extraction, validation, and enrichment, and will play a pivotal role in shaping the adoption and scaling of new AI tools and technologies across the enterprise.

Requirements

7+ years of Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education
7+ years of engineering experience with sustained hands-on design and development in Java (modern JVM stacks, microservices, distributed systems, performance engineering)
5+ years of hands-on programming and/or scripting experience in Python or other relevant languages
2+ years of experience with AI, Generative AI, or Agentic automation solutions design and development

Nice To Haves

5+ years of experience with Infrastructure as Code (IaC) implementation using Terraform, Crossplane, or other industry-equivalent solutions
5+ years of experience with OpenShift Container Platform and/or Google Cloud Platform, and/or Microsoft Azure hands-on experience
4+ experience architecting and building AI-powered solutions, including LLM integration, prompt engineering, RAG patterns, model orchestration, AI pipelines, and responsible AI practices
Hands-on experience with Vector Databases and their application in knowledge representation and retrieval
Experience with event-driven architectures (Kafka or similar)
Strong background in cloud-native architectures (containerization, orchestration, CI/CD, DevSecOps) with experience operating systems at enterprise scale
Proven experience designing large-scale distributed systems in production
Experience leading complex technology initiatives, including those that are companywide with broad impact
2+ years of experience building full stack Agentic AI Automations (from chat experiences to multi-agent systems) using Agentic AI Frameworks like LangGraph, Crew AI, Microsoft AutoGen, LangChain,etc.
Deep understanding of LLMs, prompt engineering, vector databases, and orchestration tools
Expertise in cloud AI platforms (GCP Vertex AI, Azure ML), On-Prem AIML systems, and MLOps frameworks
Strong programming skills (Python, SQL/NoSQL) and experience with ML frameworks (TensorFlow, PyTorch)
Proven track record in enterprise-scale AI deployments, model migration projects, and innovation initiatives
Exposure to Google Cloud Platform: Vertex AI / Gemini Enterprise Agent Platform, Agentspace, MCP, A2A exposure
Experience with enterprise-grade automation solutions design and implementation using tools such as Ansible, Harness CD, GitHub Actions, or Playwright
Familiarity with responsible AI principles, governance, and operating within regulated environments, including Model Risk Management (MRM) processes and controls
Experience with database technologies such as Oracle, Mongo, with 3+ years of MongoDB experience
Experience using ReactJS
Strong analytical skills with high attention to detail and accuracy
Excellent communication and stakeholder management skills, with the ability to articulate complex technical concepts to executives, regulators, partners, and engineering teams
Knowledge of Wells Fargo's internal systems and processes related to content management (e.g., ICMP, Tachyon, Capture)

Responsibilities

Act as a technical advisor to leadership to develop or influence complex applications, network, information security, database, operating systems, or web technologies 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 long-term, large-scale solutions that demand vision, creativity, innovation, advanced analytical, and inductive thinking.
Translate advanced technology experience and in-depth organizational knowledge into technical engineering solutions, aligning with business objectives and strategic technological opportunities.
Provide vision, direction, and expertise to leadership on implementing innovative and significant business solutions for the IDOCS platform.
Maintain knowledge of industry best practices and new technologies, recommending innovations that enhance operations or provide a competitive advantage to the organization.
Strategically engage with all levels of professionals and managers across the enterprise, serving as an expert advisor to leadership, particularly on AI strategy and technical decisions related to IDOCS.
Remain deeply hands-on, designing, reviewing, and occasionally coding critical components to set a high engineering bar for IDOCS. This includes leading deep technical design reviews across backend, API, and AI integration layers.
Lead by example in applying engineering rigor, automation, testing, performance optimization, and secure coding practices within the IDOCS development lifecycle.
Drive the strategy, adoption, and governance of AI and GenAI capabilities across the IDOCS organization, partnering with product, data, risk, and security teams to ensure responsible, explainable, and scalable AI solutions.
Architect scalable, secure, and compliant AI infrastructure for IDOCS across hybrid environments.
Oversee end-to-end development lifecycle for IDOCS, including feature engineering, model development, validation, deployment, and monitoring, implementing proactive, event-driven model monitoring and drift detection.
Integrate Large Language Models (LLMs), RAG pipelines, agent frameworks, and AI orchestration frameworks into enterprise Java systems and foundational IDOCS platform components.
Mentor senior engineers and architects, raising the overall technical maturity of the organization and elevating engineering rigor across the IDOCS team.