Team Description

Visa Consulting and Analytics (VCA) is the consulting arm of Visa, and drives tangible, impactful results for clients. Drawing on our expertise in consulting, data analytics, technology, payments and economics, VCA solves the most strategic problems for our clients.  VCA's core client segments include issuers, acquirers, merchants, fintech's, payment enablers and governments.

The Intelligence & Data Solutions (IDS) team at VCA consists of data scientists, analysts, and engineers who provide analytics solutions. Their goal is to leverage Visa Net, one of the largest datasets globally, to help clients enhance their performance and increase profitability.

Key Responsibilities:

• Strategic Leadership: Lead the design and execution of enterprise-scale AI/ML and Generative AI initiatives,
• driving technical vision and translating complex business challenges into innovative AI solutions that deliver
• measurable business impact.
• Contribute to end‑to‑end AI/ML and Generative AI projects, helping translate business needs into technical
• solutions and participating in model design, development, and deployment.
• Technical Architecture: Architect and oversee end-to-end AI/ML systems including large language models
• (LLMs), agentic AI frameworks, and multi-agent orchestration platforms that operate at scale across global
• infrastructure.
• Advanced Model Development: Design and implement state-of-the-art deep learning architectures, foundation
• models, and custom GenAI solutions including retrieval-augmented generation (RAG), fine-tuning strategies,
• prompt engineering frameworks, and multi-modal AI systems.
• Platform Engineering: Build and govern production-grade AI platforms with robust LLMOps, AgenticAIOps, and
• MLOps practices, ensuring scalability, reliability, security, and observability across the full ML lifecycle.
• Innovation & Research: Drive R&D initiatives exploring frontier AI technologies including reinforcement learning
• from human feedback (RLHF), chain-of-thought reasoning, tool-augmented agents, and emergent AI capabilities.
• DevOps Excellence: Champion modern DevOps and DataOps practices, implementing CI/CD pipelines,
• infrastructure-as-code, containerization (Docker/Kubernetes), and cloud-native architectures (AWS/Azure/GCP)
• for AI workloads.
• Quality & Governance: Define and enforce rigorous model validation, testing, monitoring, and governance
• standards ensuring ethical AI deployment, bias mitigation, explain ability, and regulatory compliance.
• Technical Mentorship: Lead, mentor, and upskill data science teams, establishing best practices, coding
• standards, model governance frameworks, and fostering a culture of technical excellence and continuous
• learning.

Why this is important to Visa
This role is central to shaping how our organization uses AI, Machine Learning, and Generative AI to make smarter
decisions, build scalable digital capabilities, and drive meaningful innovation. By developing full-stack data science
solutions and next-generation AI models, this role directly improves how we understand customers, streamline

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

Basic Qualifications:
6 or more years of relevant work experience with a Bachelor's Degree 

Preferred Qualifications:
6+ years of relevant AI/ML experience with demonstrated leadership in delivering enterprise-scale AI solutions
Deep expertise in Generative AI, including hands-on experience with LLMs (GPT, Claude, Llama, etc.), prompt
engineering, fine-tuning, and production deployment of GenAI applications
Proficiency of Agentic AI architectures including multi-agent systems, autonomous reasoning frameworks, tool-use agents, and workflow orchestration platforms (Bedrock, LlamaIndex, AutoGen, etc.)
Deep Learning experience with across transformer architectures, reinforcement learning, computer vision, NLP,
and time-series forecasting with frameworks like PyTorch, TensorFlow, JAX
Competency in software languages such as React for integrating AI solutions into applications or visual interfaces.
Strong DevOps and platform engineering including Kubernetes, Docker, Terraform, CI/CD pipelines,
microservices architecture, and cloud-native development (AWS SageMaker, Azure ML, GCP Vertex AI)
Production ML systems experiences such as implementing LLMOps/MLOps best practices, model monitoring,
A/B testing, feature stores, model registries, and automated retraining pipelines
Experience with Agentic systems latency reduction and also guardrails, prompt injections, red teaming etc.
Ability to communicate insights clearly to both technical and non‑technical audiences.
Strong analytical thinking, attention to detail, and commitment to data/model quality.
Demonstrated interest in learning emerging AI technologies and best practices.
Previous exposure to financial services or credit card analytics is a plus.

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.