Lead Business Execution Consultant AI & Data Engineering Specialist

Job Description

About this role:

Wells Fargo is seeking a Lead Business Execution Consultant

In this role, you will:

• Lead cross functional teams to strategize, plan, and execute a variety of programs, services and initiatives
• Drive accountability for assigned initiatives, limit risk exposure, and create efficiencies as appropriate
• Review strategic approaches and effectiveness of support function and business performance
• Perform assessments through fact finding and data requiring creative approaches to solving complex issues, and develop appropriate solutions or recommendations
• Make decisions in highly complex and multifaceted situations requiring solid understanding of business group's functional area or products, facilitate decision making and issue resolution, and support implementation of developed solutions and plans
• Collaborate and consult with members of the Business Execution team and team leaders to drive strategic initiatives
• Influence, guide and lead less experienced Strategy and Execution staff within the group

Required Qualifications:

• 5+ years of Business Execution, Implementation, or Strategic Planning experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Engineering, AI/ML, or related field.
• Hands on experiencein AI/ML engineering, with hands-on model evaluation and deployment.
• Strong programming skills in Pythonand familiarity with frameworks like TensorFlow, PyTorch, Hugging Face.
• Experience with cloud platforms(AWS, GCP, Azure) and data pipeline tools(Spark, Kafka).
• Proficiency in MLOps tools(MLflow, Kubeflow) and containerization (Docker, Kubernetes).

Preferred Experience:

• Hands-on experience with Generative AIand LLM fine-tuning.
• Knowledge of AI governance and ethical frameworks.
• Familiarity with vector databases(e.g., Pinecone, Weaviate) and RAG pipelines.
• Certifications in AI/ML engineering or cloud AI services.

Job Expectation:

• Model Evaluation & Benchmarking:
  • Assess AI models (LLMs, vision models, predictive ML) for accuracy, fairness, scalability, and cost-effectiveness.
  • Design evaluation frameworks and metrics for performance comparison across different architectures.
• Experimentation & Prototyping:
  • Rapidly prototype new AI models and techniques, including fine-tuning and hyperparameter optimization.
  • Implement Retrieval-Augmented Generation (RAG) and vector-based search for LLMs where applicable.
• Data Engineering & Pipeline Development:
  • Build and maintain scalable ETL pipelines to feed high-quality data into AI models.
  • Ensure data integrity, preprocessing, and feature engineering for optimal model performance.
• Deployment & MLOps:
  • Deploy models into production using containerization (Docker) and orchestration tools.
  • Utilize MLOps frameworks (e.g., MLflow, Kubeflow) for lifecycle management and monitoring.
• Performance Monitoring & Continuous Improvement:
  • Implement drift detection, bias monitoring, and automated retraining workflows.
  • Stay current with emerging AI technologies and integrate best practices into evaluation processes.
• Collaboration & Documentation:
  • Work with data scientists, software engineers, and product teams to align AI solutions with business objectives.
  • Maintain comprehensive documentation of evaluation methodologies, findings, and deployment strategies.

Required Skills:

• Deep understanding of AI model architectures, including LLMs, transformers, and classical ML algorithms.
• Ability to compare models across multiple dimensions(accuracy, latency, cost, interpretability).
• Expertise in data engineeringfor AI workflows, including ETL and feature engineering.
• Strong analytical and problem-solving skills with experience in statistical evaluation metrics.
• Excellent communication skills for cross-functional collaboration.

Preferred Experience:

• Hands-on experience with Generative AIand LLM fine-tuning.
• Knowledge of AI governance and ethical frameworks.
• Familiarity with vector databases(e.g., Pinecone, Weaviate) and RAG pipelines.
• Certifications in AI/ML engineering or cloud AI services.

Posting End Date:

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.

Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.