This engineering role is for a hands-on developer who will design, build, and operate distributed platform services and APIs, contributing to next-generation data infrastructure at Walmart scale. The position involves working with AI, GenAI, and agentic-powered platform capabilities, ensuring reliability, scalability, and observability.
Responsibilities
Design, build, and operate distributed platform services and APIs using Java and Python, applied against Kubernetes or equivalent cloud-native infrastructure
Apply domain-oriented design, system design, and low-level design (LLD) rigor to ambiguous platform problems, evaluating dependencies, trade-offs, failure modes, scalability, cost, and long-term durability
Flex into data engineering work when needed, contributing directly to Spark-based data pipelines and processing jobs
Build AI, GenAI, and agentic-powered platform capabilities, including intelligent developer tooling, workflow automation, agentic services, and AI-assisted operational tooling
Own platform reliability, scalability, and observability, including service-level objectives, distributed tracing, alerting, and incident response
Guide architecture and system design decisions across microservices, event-driven systems, and enterprise integrations, considering effects on downstream data engineering workloads
Partner with data engineers, data scientists, and ML engineers to ensure platform services expose the right primitives for data pipelines, feature stores, and model-serving paths
Establish engineering standards through architecture reviews, design reviews, code reviews, and production readiness reviews
As a Staff engineer, set technical direction and best practices within your team and technical domain, mentoring other engineers and influencing GDF's broader platform engineering standards
Continuously evaluate emerging platform, cloud, and AI/agentic technologies, adopting them pragmatically where they improve reliability, productivity, or business value
Requirements
Genuinely hands-on coding: 8+ years of professional software engineering experience building and operating large-scale distributed platforms
Strong proficiency in Java and Python, comfortable writing, reviewing, and debugging production code
Additional experience with Go, C++, or Scala is a plus
Operational Excellence (OE) and Engineering Excellence (EE) mindset, including SLO/SLA ownership, incident management, blameless post-incident reviews, proactive reliability and quality metrics, and continuous improvement
Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
Deep experience with microservices architectures, distributed systems, event-driven patterns, API design, service contracts, and enterprise system integration
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Strong system design, domain-oriented design (DDD), and low-level design (LLD) skills, with demonstrated ownership of production code and judgment to evaluate trade-offs, failure modes, scalability, and cost
Deep understanding of cloud-native engineering practices, including CI/CD, containerization, Kubernetes or equivalent orchestration, infrastructure automation, and production operations
Strong exposure to Big Data / data engineering technologies: Spark required at a working level, with familiarity in Hadoop/HDFS, Hive, or Kafka
Full exposure to AI and Agentic technologies: hands-on experience integrating model APIs and GenAI/LLM tooling, building or operating agentic workflows, working with embeddings/vector search, and applying MLOps practices
Strong knowledge of reliability engineering, including observability, distributed tracing, logging, metrics, alerting, incident response, capacity planning, and fault tolerance for large-scale systems
Strong grounding in security, privacy, and enterprise engineering practices, including authentication, authorization, data protection, and secure API design
Proven ability to translate ambiguous technical/business problems into clear execution plans, particularly within a newly formed team
Strong ownership mindset and technical judgment; comfortable operating with high autonomy in a 0-to-1 environment
Benefits
Flexibility for associates to manage their personal lives
Important Details
Schedule: daily work in the Bangalore office
About the Company
GDF (Global Data Foundation) is part of Walmart's AI Data organization, which builds foundational data platforms for AI, analytics, and decision-making across all Walmart banners and geographies. The newly created platform team is chartered with building next-generation data infrastructure at Walmart scale.
