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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
The Value\-Added Services Product Development (VAS PD) team drives the diversification of Visa revenue with products that differentiate Visa network and deliver valuable solutions across other networks. Risk and Security Solutions (RAS) team in VAS focuses on innovative, AI\-driven risk and fraud management solutions for issuers, merchants and fintech's.
The Sr Director of Engineering in the RAS Product Development team will be responsible for leading the technology strategy, solution, and execution of initiatives that support our business objectives. This role focuses on Integrated Risk Platform that supports all Risk and Security products such as Visa Enhanced Authentication, Decision Manager, Visa Risk Manager, Identity etc.
Essential Functions :
- Define and drive the enterprise engineering and cloud strategy, aligning with business and product goals to accelerate innovation, scalability, and time to market.
- Lead adoption of Generative AI and Agentic AI across the SDLC, delivering up to 10X developer productivity and enabling differentiated, AI‑powered business solutions.
- Provide senior technology leadership for cloud‑first platforms (AWS, Azure, GCP), ensuring systems are secure, resilient, cost‑optimized, and engineered for 5 9s\+ availability.
- Establish and enforce modern engineering excellence, including CI/CD automation, DevOps, testing, observability, and architectural standards to ensure reliability and quality at scale.
- Lead, mentor, and grow high‑performing, multi‑disciplinary engineering teams, fostering a culture of ownership, inclusion, accountability, and continuous learning.
- Partner closely with Product, Security, Privacy, and Governance leaders to define joint product and technology roadmaps and deliver compliant, scalable solutions that meet non‑functional requirements.
- Drive delivery of secure, interoperable, and fit‑for‑purpose platforms and products, balancing speed with long‑term architectural integrity and operational excellence.
- Communicate technical vision and execution plans clearly to executives and stakeholders, influencing decision‑making and aligning engineering outcomes with business KPIs and leadership principles.
This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.Qualifications
Basic Qualifications • 12\+ years of relevant work experience with a Bachelor’s Degree or at least 9 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 6 years of work experience with a PhD, OR 15\+ years of relevant work experience. Preferred Qualifications • 15 or more years of experience with a Bachelor’s Degree or 12 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, or MD), PhD with 9\+ years of experience • 15\+ years of progressive engineering experience, including 12\+ years leading large‑scale product development and delivery, with a Bachelor’s degree or higher in Computer Science, Engineering, or a related field. • Proven expertise across modern technology stacks, including Java/J2EE, GoLang, Python, Spring Boot, React, RESTful APIs, SQL/NoSQL databases, Kubernetes, Kafka, and test automation frameworks. • Demonstrated success driving measurable improvements in engineering productivity, delivery velocity, system performance, reliability, and operational excellence through data‑driven leadership. • Deep experience with cloud‑native and DevSecOps architectures, leveraging AWS and/or Azure, containerization (Docker), Kubernetes, serverless computing, and automated CI/CD pipelines. • Advanced knowledge of Generative AI and Agentic AI, including hands‑on experience integrating LLMs, vector databases, RAG, prompt engineering, and AI governance into production platforms to achieve order‑of‑magnitude productivity gains. • Strong foundation in secure‑by‑design architecture, including zero‑trust, defense‑in‑depth, and compliance‑driven engineering within highly regulated, mission‑critical environments. • Recognized architectural leadership, with experience designing and operating globally distributed, active‑active, multi‑region platforms requiring high availability, resilience, and scalability. • Exceptional leadership, communication, and strategic thinking skills, with the ability to influence at all levels, mentor senior leaders, and articulate complex technical strategies to executive and business stakeholders.U.S. Applicants Only
The estimated salary range for this position is $206,100\.00 to $ 360,800\.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 $206K-$360K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $183K across 194 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 3,708 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 $219,250 based on 424 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($283K) sits 29% above the category median. Disclosed range: $206K to $360K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Visa AI Hiring
Visa has 15 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, MLOps Engineer, Data Engineer. Positions span Foster City, CA, US, Austin, TX, US, Highlands Ranch, CO, US. Compensation range: $163K - $451K.
Location Context
AI roles in Austin pay a median of $214,343 across 87 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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