Software Engineer

Visa is a world leader in payments technology, facilitating transactions among consumers, merchants, financial institutions, and government entities globally. The Software Engineer will develop innovative payment product solutions using generative AI, modern integration patterns, APIs, and enterprise application technologies while collaborating across teams and ensuring quality, security, scalability, and resilience.

Responsibilities

Innovative Development: Engage in the design, development, and implementation of innovative software solutions, using generative AI and modern integration patterns. Contribute to a culture of innovation by actively exploring and applying new ideas and technologies

AI Solution Engineering: Support the implementation, fine-tuning, evaluation, integration, and deployment of AI components within enterprise applications, with attention to model robustness and operational quality

Collaborative Engineering: Collaborate with cross-functional teams to develop and deliver complex projects that integrate emerging technologies with our existing platforms. Work closely with Product Office, Operations & Infrastructure, Cybersecurity, Client Support, and other Product Development teams to build comprehensive solutions

Continuous Learning: Engage in continuous learning and development, actively seeking opportunities to enhance your skills and knowledge. Collaborate with peers to share insights and drive team growth

API and Integration Development: Contribute to the design and development of APIs that enhance the integration of our Payment Product applications, platforms, and solutions

Engineering Excellence: Adhere to industry best practices in software development, emphasizing quality, security, performance, scalability, availability, and resilience. Contribute to the management and reduction of technical debt within projects

Automation and Best Practices: Implement best engineering practices and automate software development, testing, and deployment processes. Ensure the timely delivery and maintenance of multiple services, focusing on continuous improvement

Preferred

skills in C++ and C# are a plus

Expertise in application security, SSDLC, and cryptography fundamentals

Self-driven and willing to work across technologies and languages

Understanding of NLP, including tokenization, word embeddings, and basic sequence models

Experience implementing and fine-tuning AI models using frameworks such as TensorFlow, PyTorch, or scikit-learn

Understanding of model compression techniques and related trade-offs

Awareness of transfer learning concepts and practical applications

Ability to design, implement, and integrate AI components into larger systems

Familiarity with common robustness issues in AI systems

Familiarity with machine learning and deep learning basics, including neural network architectures and training procedures

Exposure to machine learning operations (MLOps) and best practices for deploying AI and machine learning models

Experience with data preprocessing, feature engineering, and model evaluation techniques

Proficiency in front-end web development technologies such as ReactJS, Angular, and NodeJS

Ability to work with large datasets and perform exploratory data analysis

Expertise in multi-threading, concurrency, and error handling

Knowledge of version control, CI/CD pipelines, and best practices for deployments

Working knowledge of distributed in-memory computing technologies such as Redis

C++

C#

Application Security

SSDLC

Cryptography Fundamentals

Natural Language Processing

Tokenization

Word Embeddings

Sequence Models

TensorFlow

PyTorch

scikit-learn

AI Model Implementation

AI Model Fine-Tuning

Model Compression

Transfer Learning

AI Systems Integration

AI Robustness

Machine Learning

Deep Learning

Neural Network Architectures

Model Training

MLOps

AI Model Deployment

Data Preprocessing

Feature Engineering

Model Evaluation

ReactJS

Angular

NodeJS

Large-Scale Data Analysis

Exploratory Data Analysis

Multithreading

Concurrency

Error Handling

Version Control

CI/CD

Deployment Best Practices

Distributed In-Memory Computing

Redis

Self-Driven

Adaptability

Benefits

Potential sales incentive payments (if applicable)

Bonus and equity

Medical

Dental

Vision

401(k)

FSA/HSA

Life Insurance

Paid Time Off

Wellness Program

At least 3 days in office

Company

Digital payments network facilitating transactions worldwide

Foster City, California, USA

https://www.visa.com/

Founded in 1958

10001+ employees

Qualifications

Bachelor's degree, OR 3+ years of relevant work experience

Expert-level skills in Java, Python, and/or NodeJS

Experience building Generative AI applications, conversational AI, RAG architectures, techniques, and libraries

Skills in C++ and C# are a plus

Expertise in application security, SSDLC, and cryptography fundamentals

Self-driven and willing to work across technologies and languages

Understanding of NLP, including tokenization, word embeddings, and basic sequence models

Experience implementing and fine-tuning AI models using frameworks such as TensorFlow, PyTorch, or scikit-learn

Understanding of model compression techniques and related trade-offs

Awareness of transfer learning concepts and practical applications

Ability to design, implement, and integrate AI components into larger systems

Familiarity with common robustness issues in AI systems

Familiarity with machine learning and deep learning basics, including neural network architectures and training procedures

Exposure to machine learning operations (MLOps) and best practices for deploying AI and machine learning models

Experience with data preprocessing, feature engineering, and model evaluation techniques

Proficiency in front-end web development technologies such as ReactJS, Angular, and NodeJS

Ability to work with large datasets and perform exploratory data analysis

Expertise in multi-threading, concurrency, and error handling

Knowledge of version control, CI/CD pipelines, and best practices for deployments

Working knowledge of distributed in-memory computing technologies such as Redis

Bachelor's degree, OR 3+ years of relevant work experience.

Required skills

Represents the skills you have, click on the tags, Java, Node.js, Generative AI application development, Conversational AI, RAG architectures, Application security, SSDLC, Cryptography, NLP, TensorFlow, PyTorch, and scikit-learn

Preferred skills

skills in C++ and C# are a plus, Familiarity with common robustness issues in AI systems

Experience

3+ years