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About This Role
About Us
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.
At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.
Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.
Job Description
Are you energized by the latest advances in Generative AI and interested in helping build the next generation of intelligent applications? At Visa’s Corporate Generative AI (CGAI) team, we’re looking for early\-career developers who are eager to learn, grow, and contribute to practical AI\-driven solutions.
In this role, you’ll help contribute to well\-scoped features that support agentic workflows under guidance from senior engineers, build and support applications that use LLMs to retrieve information, automate tasks, and guide users through complex processes.
This is an opportunity to join a supportive, collaborative team working on impactful solutions across the enterprise. If you’re curious, motivated, and ready to explore applied AI while building useful, user\-centered software, we’d love to connect with you.
Essential Functions:
- Develop, test, debug, and maintain full\-stack software features across front\-end, back\-end, API, and data layers.
- Write clean, readable, and maintainable code that follows team standards and modern software engineering practices.
- Use LLMs and generative AI coding tools to support development, debugging, documentation, and problem\-solving.
- Apply computer science fundamentals, including data structures, algorithms, debugging, and object\-oriented programming.
- Participate in code reviews, incorporate feedback, and contribute to improving code quality.
- Support deployments, monitoring, and troubleshooting in Azure or similar cloud environments.
- Follow development practices including version control, testing, documentation, CI/CD, and agile work tracking.
- Collaborate with teammates and stakeholders to clarify requirements, communicate progress, and deliver high\-quality work.
- Take ownership of assigned tasks, identify blockers early, and demonstrate a strong willingness to learn.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- Bachelor's degree, OR 3\+ years of relevant work experience
Preferred Qualifications:
- 6 months of relevant work experience preferred
- Education BS/MS in Computer Science, Software Engineering or equivalent experience.
- Basic understanding of software development concepts and the Software Development Lifecycle, including development, testing, deployment, and maintenance.
- Familiarity with modern front\-end development, including HTML, CSS, JavaScript and/or TypeScript, with React preferred; understands component\-based design, reusable UI patterns, and front\-end state management concepts such as component state, shared application state, schema/model definitions, efficient data flow, and UI performance optimization.
- Exposure to back\-end development concepts and at least one server\-side programming language, such as Python, Java, C\#, or Node/TypeScript, including APIs, server\-side logic, data validation, authentication/authorization, error handling, logging, and integration with databases or external services.
- Introductory experience with relational, NoSQL, or in\-memory databases, such as PostgreSQL, MySQL, MongoDB, Redis, or similar technologies, including basic querying, data modeling, schema design, indexing concepts, data access patterns, and integration with applications or APIs.
- Introductory experience building, consuming, testing, or documenting REST APIs, including understanding HTTP methods, request/response formats, status codes, headers, authentication basics, validation, error handling, versioning concepts, and integration with front\-end applications or external services.
- Awareness of cloud platforms, such as Azure, AWS, or Google Cloud, with eagerness to learn basic cloud services and cloud\-hosted application development.
- Ability to write, review, and refine clean, readable code in one or more languages, such as Python, Java, C\#, or JavaScript/TypeScript.
- Experience using LLM\-assisted development tools to support coding, debugging, refactoring, test generation, documentation, and problem\-solving, while applying judgment to validate outputs.
- Ability to evaluate AI\-generated code critically, including assessing correctness, readability, maintainability, security, performance, edge cases, and alignment with requirements.
- Familiarity with version control systems, especially Git.
- Introductory exposure to CI/CD concepts and development workflows, including automated builds, testing, code quality checks, deployment pipelines, and release processes.
- Exposure to GenAI software development tools through academic projects, workshops, or self\-learning.
- Familiarity with basic concepts of prompt engineering and experience using language model APIs (such as Anthropic SDK, OpenAI Responses API) in academic or personal projects.
- Learning Mindset: Eager to learn core software design and best practices.
- Collaboration: Able to work well in teams and share technical ideas clearly.
- Curiosity: Interested in new technologies like Generative AI.
- Problem\-Solving: Strong analytical skills and attention to detail.
- Adaptability: Open to guidance and ready to learn new tools.
Information for US Applicants
For roles located in the US, the estimated salary range for this position is $88,000\.00 to $ 136,900\.00 USD per year, which may include potential sales incentive payments (if applicable). Salary may vary depending on job\-related factors which may include knowledge, skills, experience, and location. In addition, this position may be eligible for bonus and equity.Visa has a comprehensive benefits package for which this position may be eligible that includes Medical, Dental, Vision, 401(k), FSA/HSA, Life Insurance, Paid Time Off, and Wellness Program.Work Hours
Varies upon the needs of the department.
Travel Requirements
This position requires travel 5\-10% of the time.
Mental/Physical Requirements
This position will be performed in an office setting. The position will require the incumbent to sit and stand at a desk, communicate in person and by telephone, frequently operate standard office equipment, such as telephones and computers.
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 protect veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with the EEOC guidelines and applicable local law.
Salary Context
This $88K-$136K range is in the lower quartile for AI Software Engineer roles in our dataset (median: $185K across 231 roles with salary data).
Role Details
About This Role
AI Software Engineers build the applications and systems that AI models run inside. They own the API layers, data pipelines, frontend integrations, and infrastructure that turn a model into a product users interact with. Every AI company needs engineers who can build the software around the AI.
The challenge is building reliable systems around inherently unreliable components. Models are probabilistic. They'll give different answers to the same question. They hallucinate. They're slow. They're expensive. Your job is to build an application layer that handles all of this gracefully while delivering a product that users trust and enjoy.
Across the 4,317 AI roles we're tracking, AI Software Engineer positions make up 7% of the market. At Visa, this role fits into their broader AI and engineering organization.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
What the Work Looks Like
A typical week includes: building API endpoints that serve model inference with caching and fallback logic, designing the data pipeline that feeds context to a RAG system, implementing streaming responses in the frontend, debugging a race condition in the async inference pipeline, and optimizing database queries for the vector search layer. It's full-stack engineering with AI at the center.
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
Skills Required
Full-stack engineering skills with AI integration experience. Python and TypeScript are the most common requirements. You'll need to understand API design, database architecture, and how to build reliable systems around probabilistic outputs. Experience with streaming, async processing, and caching patterns is increasingly important as real-time AI applications proliferate.
Knowledge of vector databases, embedding APIs, and LLM integration patterns (function calling, structured outputs, retry logic) differentiates AI software engineers from general software engineers. Understanding cost optimization (caching strategies, model routing, batched inference) is valuable since inference costs can dominate application economics.
Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
Compensation Benchmarks
AI Software Engineer roles pay a median of $218,500 based on 729 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($112K) sits 49% below the category median. Disclosed range: $88K to $136K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Visa AI Hiring
Visa has 4 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Foster City, CA, US, San Francisco, CA, US, Bellevue, WA, US. Compensation range: $136K - $332K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI Software Engineer roles include Software Engineer, Full-Stack Developer, Backend Engineer.
From here, career progression typically leads toward Staff Engineer, AI Architect, Engineering Manager.
If you're a software engineer, you're already 80% there. Learn the AI integration patterns: RAG, streaming inference, function calling, structured outputs. Build a project that demonstrates you can wrap an AI model in a production-quality application with proper error handling, caching, and user experience. That's the portfolio piece that gets you hired.
What to Expect in Interviews
Technical screens look like standard software engineering interviews with an AI twist. Expect system design questions about building reliable applications around probabilistic models: handling streaming responses, implementing retry logic for API failures, and designing caching strategies for LLM outputs. Coding rounds test standard algorithms plus practical integration patterns like async processing and rate limiting.
When evaluating opportunities: Strong postings describe the product you'll be building, the AI integration patterns you'll work with, and the scale requirements. Look for companies that have existing AI features and need engineers to improve and expand them, not companies that are 'planning to add AI' someday.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
AI Software Engineer roles are among the most numerous in the AI job market. Every company deploying AI needs software engineers who understand AI integration patterns. The demand is broad, spanning startups to enterprises, across every industry adopting AI capabilities.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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