Define and drive the architectural vision for enterprise-scale platforms, with a strong emphasis on AI/ML integration, agentic systems, and intelligent automation.
Guide engineering teams across domains on best practices, technical design, and architectural decisions.
Architect resilient, cloud-native, full-stack solutions that deliver scale, performance, and security.
Collaborate closely with data scientists, ML engineers, and product teams to operationalize AI/ML models, including those based on LLMs and deep learning architectures.
Design and implement agent-based systems for proactive monitoring, triaging, and decision-making.
Influence roadmap decisions and technical strategy in collaboration with senior leadership.
Ensure high standards for quality, security, and performance through rigorous design and code reviews.
Contribute to internal platform standards, reusable frameworks, and engineering playbooks.
Champion the use of open-source and emerging technologies that align with Walmart’s innovation goals.
Partner with cross-functional teams globally to solve complex business problems with intelligent solutions.
Foster a culture of engineering excellence, mentoring senior engineers, and participating in org-wide technical forums.
Requirements
Bachelor's Degree or Master’s Degree with 10+ years of experience in Computer Science or related field with expertise in platform architecture, scalable systems, and enterprise development.
Proven leadership in designing and delivering large-scale, distributed systems.
Strong foundation in algorithms, data structures, system design, and cloud-native principles.
Deep expertise in backend development (Java, Scala, Spring Boot, Node.js, Microservices).
Full-stack experience with modern front-end frameworks (React.js, Angular, TypeScript).
Advanced proficiency in building RESTful and event-driven architectures.
Experience working with message queues (Kafka, RabbitMQ), distributed caching, and observability stacks (ELK, Grafana, Splunk).
Expertise with SQL/NoSQL data stores, schema design, and cloud data pipelines.
Solid experience with CI/CD tooling, DevOps, containerization (Docker), orchestration (Kubernetes), and deployment on cloud platforms (Azure, GCP, AWS).
Demonstrated experience integrating AI/ML capabilities into platform services —from model inference to feedback loops.
Benefits
401(k) match
Stock purchase plan
Paid maternity and parental leave
PTO
Multiple health plans
Company-paid life insurance
Short-term and long-term disability
Company discounts
Adoption and surrogacy expense reimbursement
Applicant Tracking System Keywords
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