Principal AI Engineer

Wells Fargo•Boston, MA

20h•$191,000 - $305,000•Hybrid

About The Position

Wells Fargo is seeking a Principal AI Engineer to join the CCIBT Gen AI team, which builds AI frameworks, intelligent agents, and technology platforms to enable and accelerate AI-driven capabilities across CCIBT. The role uses Generative AI to accelerate software development, enhance engineering productivity, and deliver innovative solutions. The engineer designs, develops, and deploys AI solutions using large language models (LLMs), agentic frameworks, and emerging technologies, ensuring alignment with enterprise architecture, security, risk, governance, and responsible AI standards. The ideal candidate has experience building and operationalizing AI-powered applications, with expertise in Agentic AI, fine-tuning, Retrieval-Augmented Generation (RAG), multi-agent frameworks, scalable AI platform development, and enterprise-grade AI governance and compliance. This role leads complex, enterprise-wide technical challenges and advises leadership on AI development strategies, while creating reusable components and tools for efficiency and scalability across CCIBT. The position offers a hybrid work schedule and is based at one of the listed locations in Boston, Massachusetts, or Charlotte, North Carolina. It is not eligible for visa sponsorship, and relocation assistance is not available.

Requirements

At least 7 years of engineering experience, or equivalent demonstrated through work experience, training, military experience, or education.
At least 7 years of software development experience.
At least 5 years of experience with Java, Python, OpenShift containers, and other relevant technologies.
At least 5 years of experience with AI and ML concepts, including deep learning, natural language processing, and computer vision.

Nice To Haves

Bachelor’s or master’s degree in computer science, artificial intelligence, or a related field.
Hands-on experience designing and building Generative AI and Agentic AI solutions using LLMs, multi-agent frameworks, RAG, and AI orchestration platforms.
Experience with Google Vertex AI, Microsoft 365 Copilot, Copilot Studio, LangChain, Google Agent Development Kit (ADK), AutoGen, Semantic Kernel, or similar frameworks for enterprise-grade Generative AI and Agentic AI solutions.
Strong proficiency in software engineering using Python, Java, or other modern programming languages, with experience building scalable, production-grade applications and APIs.
Experience with cloud-native architectures, microservices, containerization technologies such as Docker and Kubernetes, and CI/CD pipelines.
Knowledge of AI evaluation and benchmarking techniques, model performance assessment, and observability frameworks for production AI systems.
Excellent problem-solving and analytical skills, including the ability to troubleshoot complex technical challenges in distributed and AI-driven systems.
Ability to independently drive complex initiatives from conception to delivery with minimal guidance, navigate ambiguity, influence stakeholders, and deliver measurable business outcomes.
Strong collaboration, communication, and stakeholder management skills across engineering, product, architecture, risk, and business teams.
Ability to drive innovation, influence technical direction, and mentor engineers in modern AI and software engineering practices.

Responsibilities

Design, develop, and deploy AI applications using language models, agents, agentic frameworks, and related technologies.
Collaborate with enterprise teams to integrate LLM models with existing CCIBT products and systems.
Lead the design and development of scalable AI applications, ensuring high performance, accuracy, and reliability.
Define benchmarks and metrics to evaluate agent and agentic framework performance.
Stay current with advancements in AI, LLMs, and agentic frameworks, applying them to improve existing systems and develop new ones.
Lead the strategy and resolution of highly complex, unique challenges across multiple areas or the enterprise, delivering long-term, large-scale solutions requiring vision, creativity, innovation, and advanced analytical and inductive thinking.
Translate advanced technology experience, knowledge of business objectives and the enterprise technology environment, organizational structure, and strategic technology opportunities and requirements into technical engineering solutions.
Advise leadership to influence AI development strategies.
Create reusable components and tools to improve efficiency and scalability across CCIBT.
Follow applicable risk programs, Wells Fargo policies, and procedures; fulfill risk and compliance obligations; escalate and remediate issues; and make sound risk decisions.