The Client Services Data & AI Solutions Team builds open, trusted data and AI culture where the cost of curiosity is low, and insights are actionable. We govern transactional data and metrics, deliver usable dashboards and certified data sources, and apply analytics and AI to generate value. We partner with stakeholders, from executive leaders to customer-facing teams, ensuring data and AI assets are reliable, secure, and embedded in daily work.

In this specialist role, we are seeking a highly skilled AI Engineer to lead the development and integration of AI technologies into our Client Services operations. This role focuses on leveraging generative AI, machine learning operations (MLOps), AI model fine-tuning, enrichment pipelines to enhance service delivery and predictive capabilities.

Responsibilities:

• Establish data, AI processes and automation aligned to business and technology requirements, leveraging supported data platforms, MLOps tooling, and models.
• Build production-grade AI services: LLM-based applications, RAG pipelines, recommendation systems, forecasting, and classification
• Develop and maintain data models and schemas optimized for analytics, ML feature stores, and AI workloads.
• Deliver data engineering and AI projects end to end: ingestion, modeling, pipeline development, feature engineering, model training, deployment, and monitoring.
• Enforce best practices in data architecture and governance and provide expertise in data modeling, and MLOps.
• Collaborate with cross-functional teams to translate requirements into data and AI solutions.
• Implement data validation, quality checks, and model evaluation at each stage.
• Apply Agile principles to plan, build, test, and iterate data & AI solutions, document architectures, dictionaries, and models.
• Communicate complex data and AI concepts clearly to technical and non-technical audiences.
• Stay current on trends in cloud engineering, distributed computing, LLMs, models, databases, orchestration etc.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

Basic Qualifications:
4+ years of work experience with a bachelor’s degree in STEM field.

Preferred Qualifications:
6-12 years in data, analytics, data engineering with focus on AI.
Expertise in SQL, Python, and databases.
Proven experience with large datasets using Hadoop (Hive), Spark, Python (pandas, NumPy), Presto, and SQL.
Hands on experience using LLM ecosystems (OpenAI, Azure OpenAI, Vertex AI), fine tuning LLMs and using advanced AI techniques like RAG.
Experience designing feature stores and ML-ready datasets.
Experience with Python ML/AI frameworks (scikit-learn, PyTorch, TensorFlow).
Experience in the core machine learning workflow, including data handling (cleaning, wrangling, feature engineering) and modeling with algorithms like Linear Regression, Decision Trees, and XGBoost.
Experience with orchestration and scheduling tools such as Airflow.
Understanding of visualization tools (Tableau, QlikView, Power BI).
Strong problem solving, analytical skills, and attention to detail.
Effective communicator of statuses, issues, and risks.
Team player and collaborator, comfortable in a matrixed environment and with cross-functional delivery.

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.