Job Summary 

Walmart is a multi-national people led tech powered omnichannel retailer with over 2.2M associates. At People Support Tech, EBS we help, support and empower the Walmart’s HR function with AI and GenAI solutions to improve productivity, harnessing the opportunities for growth, focusing on well-being and cultivating cultures of belonging for all Walmart's associates. Our team is responsible for transforming the People Help Center experience that is being leveraged by 2.2M associates through different voice and chat channels.  

The vision is to deliver a radically efficient, deeply empathetic People Services experience where associates get what they need the first time—with clarity, speed, and zero unnecessary effort. By leveraging AI, the system anticipates and resolves associates’ queries on HR functions like Benefits, Payroll etc. before they become human contacts, ensuring proactive support for associates. Additionally, human agents are empowered with context, judgment support, and automation, allowing them to deliver faster, more accurate assistance while focusing on meaningful interactions. This approach enhances productivity, cultivates a culture of belonging, and completely transforms the HR Help Center Experience for all Walmart's associates. 

Our team is seeking a highly skilled and experienced Staff Software Engineer, Backend. In this hands-on individual contributor role, you will act as a senior technical leader within the team, driving the design and development of highly performant, scalable backend systems that power user-facing web and conversational experiences. You bring deep hands-on expertise in Java and Python, along with strong judgment in system design, reliability, and customer impact. You will contribute significantly to architectural decisions, lead complex technical initiatives, and help raise the engineering bar through high-quality code, thoughtful design reviews, and mentorship. The role also involves close collaboration with cross-functional partners to ensure solutions align with business goals, security requirements, and long-term scalability. 

What you’ll do 

This is a vital role with significant growth opportunities. From day one, you will be trusted to drive meaningful technical outcomes aligned with organizational goals. Key responsibilities include, but are not limited to: 

• Lead the design and development of scalable, distributed backend systems supporting AI-driven, high-traffic web and conversational applications 

• Design and build backend platforms and APIs using Java, Node.js (TypeScript), and Python that integrate with GenAI and ML services in a secure, reliable, and cost-efficient manner 

• Design, build, and operate real-time conversational and search platforms, including chatbot and virtual assistant systems, integrating rule-based logic, ML/GenAI services, and backend orchestration in production environments 

• Define and evolve service boundaries, contracts, and data flows across microservices, event-driven systems, and data-intensive workflows 

• Partner closely with machine learning engineers, applied researchers, and data scientists to productionize AI/GenAI capabilities with strong integration patterns, observability, and operational discipline 

• Lead complex technical initiatives end-to-end, contributing to design decisions, trade-off analysis, implementation, and long-term system evolution 

• Set and uphold backend engineering standards for code quality, performance, security, resiliency, and operational readiness through design and code reviews 

• Drive improvements in reliability, scalability, and performance, applying best practices in caching, concurrency, fault tolerance, rate limiting, and capacity planning 

• Establish and enhance observability practices, including logging, metrics, tracing, and alerting, to ensure systems are debuggable and resilient in production 

• Mentor and guide engineers across levels, providing technical feedback and architectural coaching while remaining deeply hands-on 

• Collaborate with product, design, and business stakeholders to translate complex requirements into robust backend solutions aligned with platform strategy 

• Support production operations, including on-call participation, incident analysis, and implementation of systemic fixes 

• Evaluate and adopt backend and AI platform technologies pragmatically to improve system capabilities and developer productivity 

What you’ll bring 

• 10+ years of professional software engineering experience, with a strong focus on building and operating large-scale backend and platform systems in production 

• Expert-level backend development experience in one or more of the following: Java/Spring Boot, Node.js/TypeScript, and Python 

• Proven experience designing distributed systems, including microservices, event-driven architectures, asynchronous processing, and data-intensive workflows 

• Experience building and scaling real-time systems, such as conversational platforms, chatbots, search, or decision-support applications in production 

• Strong understanding of real-time system constraints, including latency budgets, rate limiting, fault tolerance, and reliability under variable load 

• Strong API design expertise, including REST and/or gRPC, service contracts, backward compatibility, and integration patterns 

• Hands-on experience integrating AI/ML and GenAI services into backend systems, with an understanding of inference workflows, latency considerations, orchestration, and cost controls 

• Deep understanding of scalability, performance, and reliability engineering, including caching strategies, concurrency control, and capacity planning 

• Experience with data storage and retrieval systems, including relational and NoSQL databases, search engines, and object storage 

• Strong grounding in security fundamentals, including authentication, authorization, data protection, and secure API design 

• Experience building production-grade observability, including logging, metrics, tracing, and alerting 

• Demonstrated technical leadership, including leading design discussions, mentoring engineers, and influencing technical direction within teams 

• Operational excellence mindset, with experience supporting production systems, participating in on-call rotations, and driving post-incident improvements 

• Strong collaboration and communication skills, with the ability to work effectively across engineering, product, and ML teams 

• A strong sense of ownership and craftsmanship, with a bias toward automation, continuous improvement, and high engineering standards