Principal Engineer - AI Engineering

Principal Engineer For Tachyon Cortex Ai Engineering

Wells Fargo is seeking a Principal Engineer for Tachyon Cortex AI Engineering within the Digital Technology and Innovation organization. This organization supports the evolution of digital platforms and accelerates the integration of innovation into enterprise and customer-facing capabilities.

The Principal Engineer will provide strategic and hands-on technical leadership for the architecture, development, modernization, and operationalization of enterprise-scale predictive and generative AI solutions across hybrid and multi-cloud environments. This role requires deep engineering expertise, architectural vision, and the ability to influence complex technology decisions across multiple organizations.

The ideal candidate will be a seasoned AI/ML platform architect with proven hands-on experience designing, building, and operating enterprise AI platforms. The candidate should have expertise in AI compute environments, data engineering, cloud-native architecture, Model Development Lifecycle (MDLC), MLOps, Generative AI, Retrieval-Augmented Generation (RAG), and agentic AI systems.

The role will drive the continued evolution of the Tachyon Cortex enterprise AI/ML platform, including the modernization and migration of models from legacy and on-premises environments to secure, scalable, and compliant cloud-native platforms. The Principal Engineer will also guide enterprise architecture patterns for data and compute separation, platform integration, data protection, security, technology risk, and data governance.

In this role, you will:

• Act as a trusted technical advisor to senior leadership on highly complex AI/ML platform, application, infrastructure, data, security, and cloud engineering decisions.
• Lead the strategy and resolution of unique enterprise challenges requiring in-depth evaluation across multiple technology areas and organizations.
• Translate business objectives, enterprise technology strategy, regulatory requirements, and emerging AI capabilities into scalable engineering solutions.
• Provide vision, direction, and technical expertise for innovative, long-term, and enterprise-scale AI solutions.
• Maintain knowledge of industry practices and emerging technologies, recommending innovations that improve operational effectiveness or provide a competitive advantage.
• Strategically engage with professionals and leaders across the enterprise and influence technical decisions, architecture standards, and modernization roadmaps.

Key Responsibilities:

• Platform Architecture and Engineering Leadership
• Model Lifecycle Management
• Agentic AI Innovation
• Cross-Functional Collaboration

Required Qualifications:

• 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 or scripting experience using Python, Java, Shell scripting, or similar technologies.
• 5+ years of experience implementing Infrastructure as Code using Terraform, Crossplane, or equivalent solutions.
• 5+ years of hands-on experience with Open Shift Container Platform, Google Cloud Platform, Microsoft Azure, or comparable enterprise cloud platforms.
• 5+ years of experience designing and implementing enterprise-grade automation solutions using technologies such as Ansible, Harness CD, Git Hub Actions, Playwright, or equivalent tools.
• 2+ years of experience designing and developing AI, Generative AI, or agentic automation solutions.

Desired

Qualifications:

• Proven experience architecting, building, and operating enterprise-scale AI/ML platforms across hybrid and multi-cloud environments.
• Deep understanding of enterprise AI/ML architecture, including data and compute separation, platform interoperability, and integration patterns.
• Strong expertise in the end-to-end Model Development Lifecycle (MDLC), MLOps, model governance, monitoring, and operationalization.
• Experience with cloud AI platforms such as GCP Vertex AI, Azure ML, and enterprise on-premises AI/ML environments.
• Strong hands-on expertise in Kubernetes platforms, including Open Shift (OCP) and Google Kubernetes Engine (GKE).
• Experience designing and implementing Generative AI, RAG, Agentic AI, and multi-agent solutions.
• Knowledge of LLMs, prompt engineering, vector databases, embedding models, orchestration frameworks, MCP, and agent-to-agent architectures.
• Experience building AI solutions using frameworks such as Lang Graph, CrewAI, Microsoft Auto Gen, Lang Chain, and Chainlit.
• Strong understanding of security architecture, data protection, technology risk, regulatory compliance, and data governance controls.
• Experience delivering enterprise AI modernization and model migration initiatives from on-premises to cloud-native platforms.
• Strong programming skills in Python and SQL, with experience using machine learning frameworks such as Tensor Flow or PyTorch.
• Ability to influence technical strategy and architecture decisions across multiple…