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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.
Visa will accept applications for this role until at least 10-07-2026Job Description
Team Description
As the payments-technology landscape continues evolving at a dizzying pace, financial institutions need a strategic partner to help troubleshoot, innovate, and prepare for an increasingly competitive landscape.
The Visa Consulting & Analytics (VCA) team, part of Value-Added Services (VAS) as the consulting arm of Visa, comprises approximately two thousand payments experts, economists, data analysts, and strategists working to create tangible business growth for Visa clients. Core client segments include issuers, acquirers, merchants, fintechs, payment enablers, governments and more.
Role overview
The VCA Global Strategy & Operations (S&O) team is seeking a Manager, AI Enablement & Digital Content, who is innately curious, boldly innovative, and highly capable. The Manager will support the global S&O team in two primary capacities: advancing VCA's transformation into an AI-enabled consulting firm and supporting VCA's digital content, thought leadership, and business enablement efforts.
In capacity one, the manager will support VCA's AI transformation through the development of enablement resources, talent and learning content, transformation narratives, and AI-enabled tools and workflows that help employees build new skills and adopt new ways of working. In capacity two, they will support VCA's digital content and thought leadership efforts by creating high-quality content that showcases VCA's expertise, solutions, and market perspective, including social media content, AI- and search-optimized content, and audience-ready assets derived from research, insights, and client success stories.
The ideal candidate is an exceptional writer and storyteller, structured thinker, and proactive problem solver who keeps pace with emerging AI tools (e.g., Claude, Claude Code, ChatGPT, Microsoft Copilot, etc.). They are highly AI fluent and comfortable experimenting with new tools, building prompts, and leveraging AI agents and workflows to streamline work, create scalable content and resources, and enhance how VCA consultants work, communicate, learn, and deliver impact for Visa clients.
Key responsibilities
1. AI Enablement, Learning & Transformation Content
- Support the development of training, enablement, and learning materials, including FAQs, toolkits, guides, playbooks, resource pages, and manager materials.
- Support talent and capability-building initiatives by helping create competency guidelines, interview guides, onboarding content, and related materials.
- Develop transformation narratives, employee updates, town hall content, newsletter content, and other storytelling assets that support VCA's transition into an AI-enabled consulting firm.
- Help package AI transformation resources in ways that are easy for employees and consulting teams to find, understand, and apply.
- Leverage AI tools and capabilities (e.g., Claude, Claude Code, ChatGPT, Microsoft Copilot, etc.) to improve content development, research, synthesis, workflow efficiency, and knowledge sharing, including identifying opportunities to create AI-enabled resources, agents, and workflows.
2. Digital Content & Thought Leadership
- Write clear, engaging content that supports VCA's thought leadership strategy, AI transformation, priority solutions, and broader business objectives.
- Create digital content, including LinkedIn posts, articles, POVs, podcasts and other audience-facing assets.
- Transform research, whitepapers, client testimonials, and internal insights into compelling content that supports VCA's priority solutions and market positioning.
- Create AI- and search-optimized content that improves discoverability and amplifies VCA's expertise, solutions, and market perspective.
- Assist with digital and multimedia content creation, including video summaries, short-form content, social assets, and visually engaging materials.
Visa requires at least 3 days in office, expectations of these days will be confirmed by your Hiring Manager.
Qualifications
Basic Qualifications:
- 5 or more years of relevant work experience with a Bachelors Degree or at least 2 years of work experience with an Advanced degree (e.g. Masters, MBA, JD, MD) or 0 years of work experience with a PhD
Preferred Qualifications:
- 6 or more years of work experience with a Bachelor's Degree or 4 or more years of relevant experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or up to 3 years of relevant experience with a PhD.
- Strong curiosity and enthusiasm for AI, innovation, transformation, digital content, and new ways of working.
- Experience using AI tools such as Claude, Claude Code, ChatGPT, Microsoft Copilot, Gemini, Perplexity, or similar platforms to improve productivity, content creation, research, and workflow efficiency.
- Comfort experimenting with prompts, AI-enabled workflows, agents, and emerging AI capabilities.
- Excellent writing, editing, storytelling, and communication skills.
- Ability to simplify complex information and translate research, insights, and technical concepts into compelling content for different audiences.
- Comfort creating presentations, web-based content experiences, FAQs, toolkits, newsletters, thought leadership content, social media content, and other employee- or client-facing materials.
- Experience supporting transformation, consulting, strategy, enablement, thought leadership, digital content, communications, or related initiatives
- Strong organizational skills and ability to manage multiple deliverables across stakeholders, priorities, and deadlines.
- Basic graphic design and/or video-editing skills or willingness to learn tools like Canva, CapCut, Descript, Adobe Creative Cloud, iMovie, or similar platforms, basic understanding of digital storytelling, content formats, and brand guidelines.
Information for US Applicants
For roles located in the US, the estimated salary range for this position is $122,400 to $217,000 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, including the requirements of Article 49 of the San Francisco Police Code.
Salary Context
This $122K-$217K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Visa, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $211,950 based on 13,048 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($169K) sits 20% below the category median. Disclosed range: $122K to $217K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Visa AI Hiring
Visa has 14 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, AI Software Engineer, Data Scientist. Positions span San Francisco, CA, US, Foster City, CA, US, Ashburn, VA, US. Compensation range: $171K - $326K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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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