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About This Role
Position Summary...
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What you'll do...
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As a Distinguished AI/ML Engineer within Walmart Global Tech’s Reliability Engineering Organization, you will lead the technical development of next\-generation agentic AI systems and intelligent automation solutions that ensure mission\-critical reliability, scalability, and operational excellence across Walmart’s entire technology ecosystem. You will architect and implement cutting\-edge machine learning platforms and autonomous agents that transform how we manage change and performance, monitor, predict, and automatically resolve issues across all Walmart systems, supporting millions of associates and customers globally. Walmart Global Tech’s Reliability Engineering Organization is built with hybrid systems and software engineers who take technical ownership for change engineering, change management, performance engineering, reliability, scalability, automation, and mission\-critical issues related to uptime, availability, and rapid continuous improvement across Walmart’s e\-commerce, stores, and omni\-channel platforms. As a technical expert in this domain, you will drive the evolution of practices into AI\-powered, self\-healing, and autonomous systems built on modern technology stacks with intelligent change management and predictive performance optimization. You will also define and implement unified, intelligent, and operationally robust technical solutions and tools for Walmart Technology organizations across all channels and geographies.
About the Team The Reliability Engineering Organization at Walmart Global Tech is responsible for ensuring the reliability, availability, and performance of all systems that power the world’s largest retailer. As a Fortune \#1 company, our work impacts hundreds of millions of customers and associates globally—across every transaction, search, and interaction spanning Walmart’s digital and physical ecosystem. We are the guardians of system reliability for Walmart’s e\-commerce platform, supply chain systems, in\-store technology, financial services, and all critical business operations. Our Reliability Engineering organization is at the forefront of applying advanced AI/ML technologies to reliability challenges, building autonomous systems that can predict, prevent, and resolve issues before they impact customers or business operations. Reliability Engineering is a core engineering discipline within Walmart Global Tech, working closely with all product and engineering teams across the enterprise to ensure every system meets the highest standards of reliability, scalability, and performance. We are deeply invested in building a robust, intelligent, and highly automated technology foundation that supports Walmart’s mission to help people live better through innovation and operational excellence.
What You’ll Do AI/ML \& Agentic Systems Technical Leadership
- Architect and develop advanced agentic AI systems that autonomously manage complex reliability engineering workflows, predictive failure analysis, and self\-optimization across Walmart’s technology ecosystem.
- Design and implement multi\-agent orchestration platforms that coordinate autonomous agents for change management, capacity planning, and performance optimization across e\-commerce, supply chain, and in\-store systems.
- Build intelligent observability and monitoring platforms using ML\-driven anomaly detection, predictive analytics, and autonomous resolution across Walmart’s entire technology landscape.
- Develop self\-healing infrastructure platforms that leverage AI to predict, prevent, and automatically remediate system issues before they impact customers, associates, or business operations.
Reliability Engineering Technical Excellence
- Design, write, and build advanced tools to improve latency, availability, scalability and change management across Walmart Technology systems, including: Engineering reliability using metrics and measurements across all domains Enabling system scaling through technical solutions, automation, and process optimization Building tools and automation to prevent recurrence of failures across mission\-critical services Enhancing instrumentation to create a cohesive, end\-to\-end view of system health with particular focus on failure points
- Architect and implement fault\-tolerant systems and services across Walmart’s hybrid cloud infrastructure with emphasis on autonomous recovery and intelligent failure prediction.
- Collaborate with engineering teams and leadership to reduce mean time to detect (MTTD) and mean time to restore (MTTR) through intelligent automation and predictive capabilities.
- Partner with service owners across e\-commerce, supply chain, stores, fintech, and other domains to define SLA breach detection and change related anomalies, ensuring systems meet SLAs while maintaining optimal performance and user experience.
- Perform complex troubleshooting and analysis of large\-scale distributed systems using deep expertise in coding, algorithms, and distributed systems design.
Strategic Technical Innovation
- Partner with engineering organizations across E\-commerce, Supply Chain, Store Technology, Fintech, and Data Platforms to deliver autonomous reliability solutions using advanced machine learning, natural language processing, and computer vision.
- Drive development of MLOps and AIOps platforms that enable continuous learning, deployment, monitoring, and autonomous optimization of reliability systems.
- Innovate in agentic AI technologies for Reliability Engineering, including:
+ Large language models for automated incident response
+ Reinforcement learning agents for capacity optimization
+ Multi\-modal AI for infrastructure monitoring
+ Federated learning for cross\-domain reliability insights
- Implement advanced CI/CD pipelines for reliability platforms with automated validation, deployment, rollback, and built\-in observability.
- Establish platform engineering excellence by building reusable reliability infrastructure, intelligent monitoring platforms, and developer productivity tools.
- Provide technical mentorship and thought leadership across Walmart Technology through code reviews, design discussions, and knowledge sharing.
What You’ll Bring Education \& Experience
- Bachelor’s or Master’s degree in engineering, Computer Science, or a related field with 12\+ years of hands\-on experience in Reliability Engineering, AI/ML Engineering, or Platform Engineering.
- Proven record as a senior individual contributor influencing architecture and driving technical excellence across large organizations.
- Deep experience operating mission\-critical systems, with expertise in MTTD, MTTR, availability, change management, model performance, and autonomous system reliability.
Must\-Have Technical Experience
- Expert\-level AI/ML engineering experience, including deep learning frameworks such as TensorFlow and PyTorch and large\-scale production ML deployments.
- Advanced experience with agentic AI systems, including multi\-agent frameworks, autonomous decision\-making systems, LLM\-based agents, and agent orchestration platforms.
- Comprehensive Reliability Engineering expertise, including service management (Incident, Problem, and Change Management) and performance and capacity engineering for AI/ML systems.
- Expert\-level cloud engineering experience (Azure, GCP, AWS) with containerization (Kubernetes, Docker), serverless architectures, and cloud\-native AI services.
- Deep observability experience across distributed tracing, metrics, logs, APM, and AI\-driven anomaly detection.
- Strong platform engineering background including infrastructure as code, service mesh architectures, API gateways, and self\-service developer platforms.
Preferred Technical Experience
- MLOps and model lifecycle management using platforms such as MLflow, Kubeflow, or Seldon.
- NLP and computer vision expertise for intelligent log analysis, automated incident response, and visual infrastructure monitoring.
- Edge computing and distributed systems experience for retail stores and distribution centers.
- Real\-time streaming architectures (Kafka, Pulsar).
- Chaos engineering, fault injection, and performance optimization for large\-scale distributed systems.
- Open\-source contributions in reliability, observability, or infrastructure automation.
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 $169,000\.00 \- $338,000\.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 6 years’ experience in software engineering or related area.
Option 2: 8 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 4 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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1345 Crossman Ave, Sunnyvale, CA 94089\-1114, 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 $169K-$338K 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 ($253K) sits 8% above the category median. Disclosed range: $169K to $338K.
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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