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Wells Fargo is seeking a highly motivated Principal Engineer to design, architect, and lead Generative AI and Data Engineering initiatives within the HR Information Technology organization. This role requires a hands‑on technologist who can anchor critical initiatives to drive operational excellence and enhance employee and customer experience. The Principal Engineer will provide technical leadership across the design, development, and operationalization of Generative AI solutions, while shaping the enterprise HR data strategy. This role will oversee the architecture and delivery of scalable, secure, and resilient data engineering solutions across the HR data ecosystem, enabling advanced analytics, AI‑driven insights, and next‑generation HR capabilities. The Principal Engineer will also act as a trusted advisor to senior leadership, influencing architecture decisions, solution design, and implementation strategies to ensure alignment with business objectives, enterprise standards, and long‑term technology strategy.
Job Responsibility:
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
Requirements:
7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
7+ years of progressive engineering experience with sustained hands‑on expertise in architecture, system design, and end‑to‑end solution development
3+ years of hands‑on experience building AI/GenAI solutions, including LLM integration, prompt engineering, RAG patterns, model orchestration, AI pipelines, and responsible AI practices (governance, privacy, security, guardrails)
Demonstrated technical authority across application, data, and AI domains, influencing architecture decisions and engineering standards at enterprise scale
ability to define reference architectures and guide teams through implementation
Proven experience leading the architecture and delivery of Agentic AI platforms, leveraging LLMs, RAG pipelines, vector databases, orchestration frameworks, and agent‑to‑agent communication to enable autonomous/semi‑autonomous HR workflows, integrated with enterprise platforms such as Workday and ServiceNow
Experience designing production‑grade AI architectures that support multi‑step reasoning, tool invocation, workflow orchestration, and human‑in‑the‑loop controls, with strong focus on reliability, observability, and performance
Proven experience modernizing data platforms, including migration from legacy ecosystems to cloud‑native, lakehouse‑based architectures
Hands‑on experience building data platforms on GCP, using services such as BigQuery, Dataflow/Apache Beam, Pub/Sub, Dataproc/Spark, Cloud Storage, Cloud Composer/Airflow, Dataplex, and Data Catalog
Hands‑on experience delivering modern applications using microservices architecture, including API design, integration patterns, and secure service-to-service communication
Strong background in cloud‑native engineering (containerization, orchestration, CI/CD, DevSecOps) and experience operating systems at enterprise scale
Experience defining long‑term technology strategy and roadmaps, aligning architecture decisions and engineering execution to measurable business outcomes (productivity, cycle time reduction, risk/control improvements