below marketmost similar roles pay hereabove market
This role pays more than
78%
of similar roles. Most pay
$165,000–$253,500
— the blue band above.
At the midpoint, this role pays about
$254k
versus about
$209k
for comparable roles.
Based on 240 similar postings.
Employer
About Walmart
Walmart Inc. is the world''s largest retailer by revenue, operating a chain of hypermarkets, discount department stores, and grocery stores, as well as a growing e-commerce presence through Walmart.com. Industry: General Merchandise & Grocery Retail
Walmart currently has
825 open roles
on FindRole.
Listed pay typically runs
$121,000–$242,000
across 473 roles with salary data.
JOB TITLE: (USA) Distinguished, Software Engineer-AI/ML Engineer - Agentic Systems & Site Reliability Engineering
As a Distinguished AI/ML Engineer within the Site Reliability Engineering organization, you will lead the technical development of next-generation agentic AI systems and intelligent automation solutions. You will architect and implement cutting-edge machine learning platforms and autonomous agents designed to monitor, predict, and automatically resolve issues across the entire technology ecosystem. Your daily work involves building Tier 0 high-availability, resilient agentic platforms and multi-agent orchestration systems for automated incident response and capacity planning. You will utilize technologies including TensorFlow, PyTorch, Kubernetes, Docker, and various cloud services across Azure, GCP, and AWS. Key skills include expertise in LLMs, reinforcement learning, and distributed tracing tools like Jaeger and Prometheus to solve complex reliability challenges for e-commerce, supply chain, and financial services.
Architect and develop advanced agentic AI systems to autonomously handle complex reliability engineering workflows and predictive failure analysis.
Design and implement multi-agent orchestration platforms for automated incident response, capacity planning, and performance optimization.
Build intelligent observability and monitoring systems using ML-driven anomaly detection and autonomous incident resolution capabilities.
Develop self-healing infrastructure platforms that use AI to predict and automatically resolve system issues before they impact operations.
Engineer reliability and availability by establishing metrics, measurements, and automation tools across all Walmart technology domains.
Architect fault-tolerant systems across hybrid cloud infrastructure with a focus on autonomous recovery and intelligent failure prediction.
Define SLOs and build SLIs with service owners to ensure critical systems meet performance and availability standards.
Drive the development of MLOps and AIOps platforms to enable continuous learning and autonomous optimization of reliability systems.
What we're looking for
Bachelor's degree in Engineering, Computer Science, or related field and 12+ years of experience in SRE, AI/ML, or Platform Engineering.
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.
Option 2: 8 years’ experience in software engineering or related area.
Master’s degree in computer science, computer engineering, computer information systems, software engineering, or related area and 4 years' experience in software engineering (preferred).
Expert-level AI/ML engineering experience with deep learning frameworks like TensorFlow or PyTorch and production ML system deployment at scale.
Advanced experience with agentic AI systems, including multi-agent frameworks, autonomous decision-making, and LLM-based agents.
Comprehensive Site Reliability Engineering expertise including Service Management, Performance Engineering, and experience with mission-critical distributed systems.
Expert-level cloud engineering experience with Azure, GCP, or AWS, including Kubernetes, Docker, and serverless architectures.
Deep observability expertise with distributed tracing (Jaeger, Zipkin, OpenTelemetry) and monitoring tools like Prometheus, Grafana, and DataDog.
Platform Engineering experience with Infrastructure as Code (Terraform, CloudFormation, Pulumi) and service mesh architectures like Istio or Linkerd.
Experience in large-scale retail, e-commerce, or high-traffic consumer-facing systems (strongly preferred).
MLOps and model lifecycle management experience with tools like MLflow, Kubeflow, or Seldon (preferred).
Natural Language Processing and Computer Vision expertise for automated incident response and infrastructure monitoring (preferred).
Experience with real-time streaming and event-driven architectures using Kafka or Pulsar (preferred).
Chaos Engineering and fault injection experience across diverse system types (preferred).