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About This Role
Position Summary...
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What you'll do...
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We're hiring a Principal Engineer to lead this frontier—not building foundation models from scratch, but expertly weaving GenAI and LLMs into production e\-commerce systems that scale to billions of interactions. If you're passionate about taking cutting\-edge AI from prototype to real\-world impact, influencing architecture across teams, and shipping features that redefine how the world shops—let's talk.
About Team:
Focusing on customer, associate and business needs, this team works with Walmart International, which includes more than 5,200 retail units, operating in 23 countries such as Canada, Central America, Chile, China, India, Mexico and South Africa to name a few.
About You
- You live for code that matters. You thrive on JavaScript, Node.js, and GraphQL, embracing JS's quirks while crafting clean, functional, shippable magic. But now, you're excited to layer GenAI on top—building intelligent frontends and services that feel alive.
- You obsess over great UX powered by AI. You don't just code pixels; you design experiences where AI anticipates, delights, and empowers users—blending creativity, empathy, and technical precision.
- You're a relentless learner. You dive into emerging tech (LLMs, agents, RAG, evaluation frameworks) and turn research into production reality—whether it's frontend orchestration, backend integrations, or full\-stack AI flows.
- You master balance at scale. Performance on unpredictable networks, A/B tests with AI variants, safety/quality guardrails, rapid ecosystem shifts—you juggle it all while shipping fast and fearlessly.
- You amplify others. You mentor, build shared AI tooling, contribute to open\-source when it makes sense, and help teams level up in the GenAI era.
Things You Will Do:
As a Principal AI Engineer in Walmart International, you'll shape AI\-driven shopping across diverse markets:
- Define and drive technical strategy for GenAI\-powered experiences—architect scalable frontend/backend solutions that integrate LLMs intelligently, with rock\-solid code quality, performance, security, and observability.
- Lead development of AI\-infused features—craft React UIs with intelligent components, manage state in dynamic AI contexts (Redux \+ React Query), and build efficient GraphQL APIs that serve as the nervous system for LLM\-powered services.
- Ship and optimize GenAI/LLM features at massive scale—design APIs and service architectures that seamlessly integrate AI/ML components, handle token costs/latency/safety, and deliver measurable delight to millions.
- Refactor and evolve codebases—make them modular, maintainable, and ready for the next wave of AI innovation.
- Collaborate cross\-functionally—with product, design, UX, backend, and AI research teams—to create cohesive, magical customer experiences.
- Build internal AI best practices—create reusable tooling, evaluation frameworks, coding standards, and documentation that accelerate the entire org.
- Mentor and influence—lead code reviews, guide engineers, drive initiatives for developer productivity, and shape technical direction through influence, not just authority.
- Push boundaries—experiment with emerging GenAI techniques, contribute insights internally (and externally when possible), and own large\-scale projects that impact global e\-commerce daily.
What You'll Bring:
- 12\+ years of software engineering experience building and shipping large\-scale, production systems.
- Proven track record shipping distributed systems in Java (or equivalent high\-scale languages).
- Hands\-on experience shipping GenAI or LLM\-powered features/services as part of larger production systems.
- Strong experience designing APIs and service architectures that integrate with AI/ML components.
- Deep expertise in modern JavaScript ecosystems (React, Node.js, GraphQL) and performance optimization, testing, CI/CD.
- Demonstrated ability to influence technical direction without direct authority—through expertise, collaboration, and vision.
Preferred Qualifications
- Expertise with GenAI tools/patterns (e.g., RAG, agents, prompt orchestration, evaluation pipelines).
- Experience operationalizing LLM evaluation frameworks—including offline benchmarks, automated \+ human review loops, production monitoring for quality, safety, and business impact (nice to have, but highly valued).
- Familiarity with cloud platforms (AWS/GCP/Azure), containerization (Docker/Kubernetes), and micro\-frontends/mono\-repos (Nx).
- Track record in Agile environments with excellent communication skills.
At Walmart, we offer competitive pay as well as performance\-based bonus awards and other great benefits for a happier mind, body, and wallet. Health benefits include medical, vision and dental coverage. Financial benefits include 401(k), stock purchase and company\-paid life insurance. Paid time off benefits include PTO (including sick leave), parental leave, family care leave, bereavement, jury duty, and voting. Other benefits include short\-term and long\-term disability, company discounts, Military Leave Pay, adoption and surrogacy expense reimbursement, and more. You will also receive PTO and/or PPTO that can be used for vacation, sick leave, holidays, or other purposes. The amount you receive depends on your job classification and length of employment. It will meet or exceed the requirements of paid sick leave laws, where applicable. For information about PTO, see https://one.walmart.com/notices. Live Better U is a Walmart\-paid education benefit program for full\-time and part\-time associates in Walmart and Sam's Club facilities. Programs range from high school completion to bachelor's degrees, including English Language Learning and short\-form certificates. Tuition, books, and fees are completely paid for by Walmart.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to a specific plan or program terms.
For information about benefits and eligibility, see One.Walmart.
The annual salary range for this position is $143,000\.00 \- $286,000\.00 Additional compensation includes annual or quarterly performance bonuses. Additional compensation for certain positions may also include :
- Stock
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Minimum Qualifications...
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*Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.*
Option 1: Bachelor's degree in computer science, computer engineering, computer information systems, software engineering, or related area and 5 years’ experience in software engineering or related area.
Option 2: 7 years’ experience in software engineering or related area.Preferred Qualifications...
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*Outlined below are the optional preferred qualifications for this position. If none are listed, there are no preferred qualifications.*
Master’s degree in computer science, computer engineering, computer information systems, software engineering, or related area and 3 years' experience in software engineering or related area., We value candidates with a background in creating inclusive digital experiences, demonstrating knowledge in implementing Web Content Accessibility Guidelines (WCAG) 2\.2 AA standards, assistive technologies, and integrating digital accessibility seamlessly. The ideal candidate would have knowledge of accessibility best practices and join us as we continue to create accessible products and services following Walmart’s accessibility standards and guidelines for supporting an inclusive culture.Primary Location...
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815 Eleventh Ave, Sunnyvale, CA 94089\-4731, United States of America
Walmart and its subsidiaries are committed to maintaining a drug\-free workplace and has a no tolerance policy regarding the use of illegal drugs and alcohol on the job. This policy applies to all employees and aims to create a safe and productive work environment.
Salary Context
This $143K-$286K range is above the 75th percentile for AI Software Engineer roles in our dataset (median: $189K across 518 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 26,159 AI roles we're tracking, AI Software Engineer positions make up 2% of the market. At Walmart, 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 $235,100 based on 665 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($214K) sits 9% below the category median. Disclosed range: $143K to $286K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Walmart AI Hiring
Walmart has 36 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, AI Software Engineer. Positions span Bentonville, AR, US, Sunnyvale, CA, US, Elwood, IL, US. Compensation range: $79K - $370K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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