Position Summary...What you'll do...As a
Staff Software Engineer, you'll be a technical leader who defines the direction for and evolves the
backend microservices, data pipelines, and
ML-serving infrastructure that power search at massive scale. You'll lead a team of 6-10 engineers, set the technical vision for critical systems, create clarity from ambiguity on complex cross-functional initiatives, and drive the quality bar across the team. You'll spend your days writing and reviewing code, leading design discussions, and making the architectural decisions that shape the next generation of Walmart Search. Your work will shape how hundreds of millions of customers discover products every day.
We're in an active phase of platform modernization - redesigning and refactoring core systems. If you want to build, not just maintain, this is the right time to join.
About Team:The eCommerce Search engineering team owns the end-to-end technology stack that powers product search and discovery across Walmart's global eCommerce channels, backed by microservices, large-scale data and feature pipelines, search engines, and ML model serving infrastructure. We handle millions of queries per day, and every improvement to our systems directly impacts how customers find what they need.
Our systems tackle an advanced set of problems in the search domain:
- Query & Intent Understanding - Query classification, product type prediction, intent recognition, and sequence tagging using classical ML, NLP, and deep learning techniques.
- Autocomplete - Real-time query suggestions at low-latency, high-throughput scale.
Retrieval & Search Execution - Complex query construction, faceted navigation, semantic and vector-based retrieval, and result orchestration across search engines. - Multi-phase Ranking - ML-powered ranking models that optimize for customer satisfaction and business outcomes across multiple ranking stages, using learn to rank and neural models.
- Data & Feature Pipelines - Large-scale pipelines that feed search indices, feature stores, and analytics platforms.
What you'll do: - Define the technical direction and drive the architecture for mission-critical search microservices - spanning Core Orchestration, Query Understanding, Autocomplete, Facet & Navigation, Ranking, and more.
- Design, build, and optimize high-throughput, low-latency backend services, applying best practices around distributed systems, fault tolerance, horizontal scalability, concurrency, and performance tuning.
- Design and build high-scale data and feature pipelines that process data through transformation and aggregation layers into downstream data stores, search indices, and feature stores.
- Architect complex query patterns and integrations with search engines to power relevance, ranking, and retrieval at scale.
- Lead discovery and design phases for medium-to-large initiatives - partnering with product management, data science, and UX to translate business requirements into scalable technical solutions; build cross-functional alignment, drive proof-of-concepts, and validate ideas through prototypes.
- Design and run A/B experiments to validate search improvements; use data-driven analysis and continuous monitoring to measure the impact on customer engagement and business metrics.
- Technically lead a team of 6-10 engineers, including collaboration with offshore/distributed team members - providing architectural guidance, conducting design and code reviews, identifying and removing blockers, and setting the quality bar for the team.
- Mentor and grow engineers across experience levels; drive a culture of engineering excellence through knowledge-sharing, disciplined testing practices, and thoughtful documentation.
- Collaborate with data scientists to productionize ML models for ranking and query understanding; contribute to MLOps practices, feature store development, and model serving optimization for latency and throughput in production.
- Build and maintain observability, monitoring, and alerting for search services; participate in on-call rotations and own the reliability of Search platform services in production - troubleshoot issues with urgency, perform root cause analysis, and build preventive measures.
- Contribute to long-range technical roadmaps and communicate technical strategy to senior leadership; resolve cross-team technology disagreements through informed discussion and represent the team in org-level architectural decisions.
Stay current with industry research and emerging technologies in search, distributed systems, and ML to inform the team's technical direction. - Work boldly with a sense of urgency - embrace mistakes, learn from them quickly, and drive the team toward success.
What you'll bring: - 10+ years, of experience designing, developing, and shipping production code in large-scale distributed systems.
- Deep expertise in backend development with Java and Spring Boot - strong fundamentals in object-oriented design, concurrency, and performance optimization.
- Proven track record building cloud-native, high-throughput microservices - including RESTful API design, fault tolerance patterns, and horizontal scaling - deployed on Kubernetes.
- Hands-on experience designing and building data and feature pipelines at scale using Apache Spark (including SparkSQL), working with streaming platforms like Kafka, and NoSQL databases like Cassandra.
- Demonstrated ability to technically lead teams of 6-10 engineers - setting architectural direction, mentoring, and raising the quality bar through design and code reviews.
- A disciplined, test-driven approach to development - you're well-versed in testing frameworks (JUnit, Mockito) and bring a genuine commitment to code quality, testability, and documentation.
- Strong communication skills - able to create clarity from ambiguity, articulate technical trade-offs to both engineering peers and non-technical stakeholders, and influence across teams.
- Proficiency in big data processing and analytics using technologies such as Hive, BigQuery, GCP/GCS, or equivalent.
- Familiarity with NoSQL databases (Cassandra, Cosmos DB), distributed caching, and cloud object storage (Azure Blob Storage).
- Track record of refactoring, redesigning, or rewriting existing high-scale applications is a plus - we are actively modernizing our search platform.
Preferred Qualifications:
- Experience with search engines (Solr, Elasticsearch, Vespa) or similar information retrieval systems, including vector search and embedding-based retrieval (e.g., FAISS, ANN indexes), and familiarity with search domain concepts such as query understanding, retrieval strategies, multi-phase ranking, and relevance optimization.
- Background in machine learning - including core concepts (classification, regression, neural networks, transformer-based models, LLMs), hands-on experience with frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost), and an understanding of the full model lifecycle from training through production serving.
- Hands-on work with ML infrastructure in production - including MLOps practices, model serving optimization (dynamic batching, TensorRT, ONNX, quantization), and building training and inference pipelines at scale.
- Proficiency in Python for data engineering, ML prototyping, or production scripting.
- Familiarity with cloud data platforms and orchestration tools such as GCP, BigQuery, and Airflow.
Minimum Qualifications...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 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, 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...815 Eleventh Ave, Sunnyvale, CA 94089-4731, United States of America
