Sr. Manager - AI and Data Engineering

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose – to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

The Senior Manager of AI Engineering & Data Engineering will lead the design, development, and deployment of scalable AI/ML and data solutions that enhance the operational capabilities of Visa’s Client Services organization. This role combines hands‑on technical leadership with people management and is responsible for delivering high‑impact AI systems, modern data pipelines, and analytical platforms that support service excellence at Visa.

This leader will oversee a team of AI engineers, machine learning engineers, and data engineers responsible for building production‑grade AI models, optimizing data infrastructure, and delivering automation, intelligence, and insights across CS workflows. The ideal candidate brings deep experience in data engineering, practical AI implementation, and modern ML technologies, along with a strong ability to translate business needs into technical solutions.

Key Responsibilities

AI Engineering & Applied Machine Learning

• Architect, develop, and deploy production‑ready AI/ML systems, including LLM‑based solutions, NLP models, forecasting models, and classification systems.

• Build and maintain scalable model training, evaluation, and inference pipelines aligned with Visa’s AI governance, security, and reliability standards.
• Implement retrieval‑augmented generation (RAG), vector databases, prompt engineering, and other modern AI engineering techniques to drive automation and intelligence in Client Services.
• Ensure models meet operational requirements including accuracy, performance, fairness, uptime, and continuous monitoring.

Data Engineering & Platform Development

• Lead the development of robust, scalable data pipelines to support AI/ML, analytics, and operational reporting.
• Oversee data modeling, data quality frameworks, lineage tracking, and observability across critical Client Services datasets.
• Integrate structured and unstructured data sources into Visa’s enterprise data ecosystem to enable AI solutions at scale.
• Partner with enterprise data teams to align on data governance, standards, and best practices.

Technical Leadership & People Management

• Manage and mentor a team of AI and data engineers, fostering strong engineering practices, code quality, and knowledge sharing.
• Perform architectural reviews, provide technical guidance, and enable the team to deliver high‑quality, reliable solutions.
• Drive sprint planning, resource allocation, backlog prioritization, and delivery management for end‑to‑end AI and data initiatives.
• Build a culture of innovation, experimentation, accountability, and continuous improvement.

Business Partnering & Cross‑Functional Collaboration

• Work closely with leaders across Client Services to identify opportunities where AI and data engineering can reduce operational friction and improve client outcomes.
• Communicate technical roadmaps, risks, dependencies, and impact to stakeholders and senior leadership.
• Collaborate with Product, Technology, and Enterprise AI partners to align on architectural strategies and shared platforms.
• Translate business requirements into actionable technical designs and measurable success metrics.

Operational Excellence

• Ensure solutions follow Visa’s compliance, privacy, and risk standards.
• Establish model and data reliability practices including automated testing, observability dashboards, monitoring, and alerting.
• Drive continuous optimization of performance, cost efficiency, and scalability of AI and data infrastructure.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Basic Qualifications 8–9+ years of experience in data engineering, AI engineering, or machine learning, with increasing technical and leadership responsibilities. 3–4+ years of hands‑on AI engineering experience, including building and deploying production AI/ML systems. Strong proficiency in: Python (core + ML ecosystem), SQL, and distributed data technologies. AI/ML frameworks such as TensorFlow, PyTorch, Scikit‑learn, and LLM‑related toolchains. Data engineering tools such as Spark, Airflow, Databricks or similar. Cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Experience implementing MLOps practices using CI/CD, model monitoring, feature stores, experiment tracking, and automated deployment pipelines. Proven ability to lead teams and deliver complex, multi‑stakeholder technology projects end‑to‑end. Demonstrated ability to work with ambiguity, influence without authority, and operate in a matrixed enterprise environment. Preferred Qualifications Experience with LLMs, RAG architectures, embeddings, vector search, and prompt engineering. Familiarity with enterprise‑scale data security, privacy, and governance frameworks. Knowledge of operational workflows and data needs within client services, customer operations, or financial services. Bachelor's degree in computer science, Engineering, Data Science, or related field.

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.