About the role
Responsibilities:
- Define and own the end-to-end technical architecture for the Warehouse Management System (WMS) platform services.
- Author and champion Architecture Decision Records (ADRs) and design documents that set standards across the WMS platform.
- Identify and proactively address systemic risks, single points of failure, scaling bottlenecks, data integrity gaps, and technical debt accumulation before they become incidents.
- Represent WMS in cross-org architectural forums and drive alignment with shared platform teams (cloud infra and data platform teams).
- Own data modeling and persistence strategies across SQL and No-SQL databases.
- Drive AI-assisted spec generation workflows, using LLMs to translate product requirements and domain narratives into structured API specs and champion spec-first engineering across WMS.
- Design and build scalable, high-throughput, and low-latency Java-based microservices deployed on the cloud; build microservices with domain-driven design, event-driven patterns (Kafka), and API-first principles.
- Design resilient distributed systems applying patterns such as orchestration, outbox pattern, circuit breaking, and idempotency across async workflows.
- Implement gRPC and REST APIs with strict OpenAPI contracts, backward-compatibility guarantees, and consumer-driven contract testing.
- Establish frontend architecture standards for the WMS team; component library governance, state management patterns, accessibility compliance, and performance budgets.
- Design and build full-stack features using modern frontend frameworks (React, Node, and Express JS) integrated with RESTful/GraphQL APIs.
- Design with a platform-first mindset; design shared and extensible capabilities that empower multiple teams to move faster without duplicating effort.
- Author and maintain Concord pipelines for CI/CD automation; build, test, canary deploy, and rollback orchestration across WMS microservices.
- Drive security compliance for all WMS deployments, keeping code compliant with enterprise standards, identifying and remediating security vulnerabilities.
- Implement observability-first engineering: structured logging, distributed tracing, and tracking through dashboards and alerts.
- Mentor and technically sponsor senior and mid-level engineers; conduct architecture reviews, pair on complex problems, and provide structured feedback on design documents and PRs.
- Lead engineering excellence initiatives; test coverage uplift, latency reduction programs, incident retrospectives, and platform reliability improvements.
- Champion a culture of continuous innovation; actively identify and propose improvements to development workflows and supply chain processes that reduce friction and create measurable business value.
- Address complex problems quickly and efficiently in a high-impact environment.
Requirements:
- Engineering degree in computer science or a related technical field.
- 12+ years of relevant experience in building cloud-based, highly resilient, and scalable systems.
- Excellent technical knowledge in object-oriented programming and frameworks: Java 17/21, Spring Boot, microservices, REST API, Kafka, relational and NoSQL databases, React, and Node.js .
- Expert-level understanding of software fundamentals, data structures, algorithms, problem-solving, and agile principles.
- Advanced-level exposure to cloud infrastructure, such as Azure, GCP, or AWS, and containerization ecosystems such as Docker and Kubernetes.
- AI/ML Exposure: Integrating ML model APIs/inference endpoints into production services; experience with GenAI tool adoption.
- Ability to troubleshoot issues quickly and provide technical solutions to fix those issues.
- Exceptional communication and interpersonal skills—including negotiation, facilitation, and consensus-building skills.