STAFF, SOFTWARE ENGINEER

Position Summary...

What you'll do...

About the Team

You will be part of an Engineering team that builds and operates scalable, intelligent data platforms enabling analytics, automation, and AI-driven decision-making across the organization in the FinTech space. Our work focuses on designing high-performance data systems, ensuring reliability and operational excellence, and integrating Generative AI capabilities to enhance how data is processed, understood, and used.

We work at the intersection of data engineering and applied AI — developing production-grade systems that handle data at scale, automate complex workflows, and drive measurable business impact. AI is a force multiplier for us, not an afterthought, and we expect our engineers to be both great software craftspeople and AI-aware practitioners.

Walmart's Corporate Tech & Services (CTS) is a powerhouse of several exceptional teams delivering world-class technology solutions and services making a profound impact at every level of Walmart. As a key part of Walmart Global Tech, our teams set the bar for operational excellence and leverage emerging technology to support millions of customers, associates, and stakeholders worldwide.

What You Will Do

System Design & Software Engineering Leadership

Architect Systems at Scale: Design large-scale, distributed architectures capable of processing massive datasets, supporting real-time and batch processing, and integrating AI-driven workflows seamlessly.

Drive End-to-End Execution: Own the full product lifecycle — design, development, containerization, deployment, and production operations — across diverse environments using Kubernetes, Terraform, and CI/CD pipelines.

Define Engineering Standards: Set and enforce best practices around code quality, system design, observability, scalability, and operational readiness across both core software and AI-powered components.

Lead Infrastructure Decisions: Guide data modeling, system integrations, and cloud architecture design on Google Cloud Platform (GCP) and related technologies.

Champion Observability & Reliability: Establish end-to-end monitoring frameworks (Prometheus, Grafana, OpenTelemetry) for data services and AI workloads, ensuring deep traceability and high service reliability.

Full-Stack Software Engineering

Build Robust Backend Services: Design and develop production-grade microservices and REST/gRPC APIs using Java and Spring Boot — with strong emphasis on security, performance tuning, and fault tolerance.

Develop Responsive Front-End Experiences: Architect and deliver scalable React applications, applying component-driven design, efficient state management, and seamless integration with backend services and APIs.

Design and Operate Event-Driven Systems: Model complex business domains using event-driven patterns — event sourcing, CQRS, and pub/sub — leveraging Apache Kafka to build high-throughput, fault-tolerant streaming pipelines that decouple services and enable reliable, real-time data flows.

Build High-Performance Data Processing Pipelines: Design and develop large-scale distributed data processing workloads using Scala and Spark, optimized for throughput, latency, and cost efficiency across batch and streaming use cases.

Implement Real-Time Stream Processing: Build low-latency, stateful stream processing applications using Spark Streaming, Flink, or equivalent frameworks — handling complex event patterns, windowing, and exactly-once semantics in production.

Orchestrate Complex Workflows: Architect and maintain data workflow orchestration using Airflow or equivalent, ensuring reliable scheduling, dependency management, and failure recovery across multi-stage pipelines.

Own Data Modelling and Query Optimisation: Design efficient schemas and write complex analytical queries optimised for performance across relational (PostgreSQL, MySQL) and columnar (BigQuery, Redshift) engines.

Drive Full-Stack Delivery: Partner with product and design to translate requirements into end-to-end features — owning everything from database schema through API contract to polished UI — ensuring consistent quality and operational readiness across the stack.

AI-Augmented Engineering

Integrate GenAI Capabilities: Design and ship AI-augmented features within data and application systems — LLM-powered services, intelligent automation workflows, and retrieval-augmented generation (RAG) pipelines where they add measurable business value.

Build and Evaluate AI Components: Own the integration of LLM APIs (OpenAI, Anthropic, or open-source equivalents) into production services, including evaluation frameworks, latency optimization, and cost governance.

Apply Agentic Patterns Thoughtfully: Leverage agentic orchestration frameworks (LangChain, LangGraph) to build targeted AI workflows that complement — not replace — robust software engineering foundations.

Ensure Responsible AI Practices: Embed responsible AI principles into your work — prompt governance, output auditing, bias awareness, and model versioning as first-class engineering concerns.

Collaboration & Mentorship

Mentor Engineers: Provide technical mentorship to senior and mid-level engineers, fostering a culture of innovation, ownership, and operational excellence.

Cross-Functional Partnership: Partner closely with Product, Data Science, and Principal Engineering teams to align AI initiatives with data engineering objectives, ensuring production reliability and scalability.

Champion Operational Efficiency: Identify and automate pain points in deployment, scaling, and monitoring. Drive continuous improvement in system reliability, performance, and developer productivity.

Contribute to Engineering Community: Actively participate in design reviews, architectural RFCs, code reviews, internal knowledge bases, and cross-team forums.
 

What You Will Bring

Must Have

• 10+ years of experience in Software Engineering, with demonstrated strength across the full stack — from responsive front-end interfaces and robust backend APIs to distributed data systems, cloud infrastructure, and production-grade operations.
• Deep expertise in Scala for high-performance backend and data workloads.
• Strong proficiency with Apache Spark for large-scale distributed data processing.
• Java & Spring Boot proficiency — build robust, production-grade microservices and REST APIs using Spring Boot, with strong command of dependency injection, Spring Security, and performance tuning.
• React expertise — develop responsive, component-driven front-end applications with strong understanding of state management, hooks, and integrating with backend APIs in a full-stack context.
• Apache Kafka expertise — design and operate high-throughput, fault-tolerant event streaming pipelines, including topic management, consumer group tuning, and producer reliability patterns.
• Streaming systems proficiency — hands-on experience building low-latency, stateful stream processing applications using Spark Streaming, Flink, or equivalent frameworks in production at scale.
• Event-driven architecture design — proven ability to model complex domains using event-driven patterns (event sourcing, CQRS, pub/sub) that decouple services and enable reliable, scalable system interactions.
• Strong SQL and data modelling skills — write complex analytical queries, design efficient schemas, and optimize query performance across both relational (PostgreSQL, MySQL) and columnar (BigQuery, Redshift) engines.
• Cloud infrastructure optimization — hands-on experience right-sizing compute, storage, and networking resources on GCP (or equivalent) to maximize performance while actively reducing cloud spend.
• Expertise in Kubernetes (scheduling, scaling, service orchestration) and containerization practices.
• Proficiency with Terraform for cloud infrastructure provisioning and management.
• Solid CI/CD and cloud-native operations experience — you own production, not just code.
• Working knowledge of GCP — BigQuery, Cloud Run, GCS, and related services.
• Strong observability mindset — structured logging, distributed tracing, SLO/SLA definition, and alerting across microservices and data services.
• Knowledge of Airflow or an equivalent orchestration platform for data pipeline management.
• Good working knowledge of Python — scripting, automation, and integration with AI/ML libraries.
• Familiarity with LLMs and GenAI primitives — you understand how LLM APIs work, what RAG is and when to apply it, and how to integrate AI components into production systems without them becoming liabilities.
• Strong engineering fundamentals — distributed systems, API design, testing strategy, and system observability are table stakes.
• Good to Have
• Hands-on experience with LangChain and/or LangGraph for building agentic workflows or AI orchestration pipelines.
• Experience integrating LLM APIs (OpenAI, Anthropic, open-source via HuggingFace/vLLM) into production services under real traffic and latency requirements.
• Familiarity with vector databases and embedding pipelines (Milvus, Weaviate, Pinecone) for RAG applications.
• Exposure to MCP (Model Context Protocol) for connecting AI agents to enterprise data sources and internal APIs.
• Experience in FinTech, payments, or regulated domains where production reliability, audit trails, and compliance are non-negotiable.
• Contributions to engineering communities — internal talks, blog posts, mentorship programs, or open-source projects.
• Familiarity with open-source LLM serving frameworks (vLLM, Ollama, TGI) and model fine-tuning or PEFT workflows.

Engineering Philosophy

The ideal candidate is, first and foremost, a great software engineer — someone who writes clean, maintainable, observable code and thinks deeply about system design, scalability, and reliability. On top of that foundation, they bring practical AI fluency: the ability to evaluate when AI adds genuine value, integrate LLM components responsibly into production systems, and apply emerging patterns (RAG, agentic workflows) with engineering rigor rather than hype.

We are not looking for a pure AI researcher or a GenAI specialist who treats infrastructure as an afterthought. We are looking for a builder who can architect, ship, operate, and continuously improve complex systems — and who can confidently extend those systems with AI capabilities as the problem demands.

About Walmart Global Tech
Imagine working in an environment where one line of code can make life easier for hundreds of millions of people.  That’s what we do at Walmart Global Tech. We’re a team of software engineers, data scientists, cybersecurity expert's and service professionals within the world’s leading retailer who make an epic impact and are at the forefront of the next retail disruption. People are why we innovate, and people power our innovations. We are people-led and tech-empowered.

We train our team in the skillsets of the future and bring in experts like you to help us grow. We have roles for those chasing their first opportunity as well as those looking for the opportunity that will define their career. Here, you can kickstart a great career in tech, gain new skills and experience for virtually every industry, or leverage your expertise to innovate at scale, impact millions and reimagine the future of retail.

Walmart’s culture sets us apart, and we know being together helps us innovate, learn and grow great careers. This role is based in our Bangalore office for daily work, with the flexibility for associates to manage their personal lives.

Benefits

Beyond our great compensation package, you can receive incentive awards for your performance. Other great perks include a host of best-in-class benefits maternity and parental leave, PTO, health benefits, and much more.

Belonging

We aim to create a culture where every associate feels valued for who they are, rooted in respect for the individual. Our goal is to foster a sense of belonging, to create opportunities for all our associates, customers and suppliers, and to be a Walmart for everyone.

At Walmart, our vision is "everyone included." By fostering a workplace culture where everyone is—and feels—included, everyone wins. Our associates and customers reflect the makeup of all 19 countries where we operate. By making Walmart a welcoming place where all people feel like they belong, we’re able to engage associates, strengthen our business, improve our ability to serve customers, and support the communities where we operate.

Equal Opportunity Employer

Walmart, Inc., is an Equal Opportunities Employer – By Choice. We believe we are best equipped to help our associates, customers and the communities we serve live better when we really know them. That means understanding, respecting and valuing unique styles, experiences, identities, ideas and opinions – while being inclusive of all people.

Minimum Qualifications...

Outlined below are the required minimum qualifications for this position. If none are listed, there are no minimum qualifications.

Minimum Qualifications:Option 1: Bachelor'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.Option 2: 6 years’ experience in software engineering or related area.

Preferred Qualifications...

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 2 years' experience in software engineering or related area

Primary Location...

Block- 1, Prestige Tech Pacific Park, Kadubeesanahalli Village, Varthur Hobli , India