Principal Engineer - Machine Learning & Inference Engineering

Wells Fargo•Concord, CA

1d•Onsite

About The Position

Wells Fargo is seeking a Principal Engineer in the Digital Technology and Innovation group which supports evolving digital platforms and enhances integration of the innovation pipeline into our customer-facing capabilities. The Principal Engineer for Tachyon AI Engineering will lead the design, development, and operationalization of enterprise-scale AI/ML solutions across hybrid environments. This role requires deep technical expertise, strategic vision, and leadership to accelerate predictive and generative AI adoption. The ideal candidate will have experience with AI Compute Environment, Data Engineering, Generative AI, RAG pipelines, and agentic AI systems, and will drive innovation and modernization initiatives, including model migration from on-prem platforms to cloud-native environments.

Requirements

7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of hands-on programming and/or scripting experience in one or more of the following: Python, Java, Shell scripting etc.
5+ years of experience with Infrastructure as code (IaC) implementation using Terraform, Crossplane or any other industry equivalent solutions
5+ years of experience with OpenShift Container Platform and/or Google Cloud Platform, and/or Microsoft Azure hands on experience
5+ years of experience with enterprise-grade automation solutions design and implementation experience using tools such as Ansible, Harness CD, GitHub Actions, Playwright etc.
2+ years of experience with AI, Gen AI, Agentic automation solutions design and development

Nice To Haves

Excellent communication and stakeholder management skills.
Demonstrated ability to lead complex projects with limited supervision and high accountability
Experience with Generative AI, RAG pipelines, and agentic AI systems.
Exposure to Google Cloud Platform: Vertex AI / Gemini Enterprise Agent Platform, Agentspace, MCP, A2A exposure
Cloud certification; AWS, GCP, Azure or Generative AI Leader
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
2+ years of experience building full stack Agentic AI Automations (from chat experiences to muti-agent systems) using Agentic AI Frameworks like LangGraph, Crew AI, Microsoft AutoGen, LangChain, Chainlit

Responsibilities

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
Drive the evolution of the Tachyon Predictive AI Platform on GCP Vertex AI, Azure ML, and On-Prem AIML Platform
Architect scalable, secure, and compliant AI/ML infrastructure across hybrid environments
Oversee end-to-end ML lifecycle: feature engineering, model development, validation, deployment, and monitoring
Implement proactive, event-driven model monitoring and drift detection
Lead model migration initiatives from legacy and on-prem systems to cloud-native platforms
Ensure smooth transitions with minimal downtime and compliance adherence
Drive initiatives for Generative AI and agentic AI integration into workflows
Automate governance processes and optimize operational SLAs
Partner with data scientists, MLOps engineers, and application teams to deliver AI solutions
Act as a trusted advisor to senior leadership on AI strategy and technical decisions
Provide technical guidance and mentorship to engineering teams.
Represent the organization in AI forums and contribute to enterprise AI strategy.