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DirectorFull-timeMicroservicesMachine LearningData ScienceGitAIAPI
Salary Range
$40,800 - $55,200 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data and AI Platform Engineer to join Visa's Data and Artificial Intelligence Platform (DAP) group. This role involves designing, developing, and implementing next-generation data platforms to drive incremental revenue in the digital payment industry.
Key Responsibilities
- →Lead the design, development, and deployment of GenAI solutions, including LLM integration, prompt engineering, RAG systems, and domain-specific model customization.
- →Evaluate emerging AI capabilities and prototype innovative solutions to accelerate business transformation.
- →Drive experimentation frameworks that validate model performance, user experience impact, and production feasibility.
- →Architect and build data-intensive analytical applications that enable real-time insights, predictive intelligence, and automated decisioning.
- →Partner with data engineering teams to design scalable data pipelines, metadata systems, and high-quality feature stores.
- →Architect cloud-native applications capable of handling large-scale, high-availability workloads.
- →Oversee performance optimization, distributed processing, caching strategies, and operational monitoring.
- →Design and evolve microservices architectures using best practices such as domain-driven design, event-driven patterns, and API-first development.
- →Implement robust inter-service communication (REST, gRPC, messaging) and reliability patterns (circuit breakers, rate limiting).
- →Mentor engineering and data science teams in modern AI, GenAI adoption, and architectural excellence.
- →Translate business goals into actionable engineering roadmaps and AI solution blueprints.
- →Define coding standards, architecture guidelines, model governance, and delivery best practices.
- →Collaborate closely with product, security, and platform teams to align AI solutions with enterprise strategy.
Requirements
- ✓Strong background in Generative AI and Machine Learning.
- ✓Experience with LLM integration and prompt engineering.
- ✓Proficiency in designing and building data-intensive analytical applications.
- ✓Knowledge of cloud-native application development and large-scale workloads.
- ✓Familiarity with microservices architecture and best practices.
- ✓Experience with REST, gRPC, and messaging protocols.
- ✓Strong problem-solving and analytical skills.
- ✓Excellent communication and collaboration abilities.
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