Fullstack Developer Senior

This is a remote position. We are looking   for a   Senior Full Stack   Engineer   to join the   Finance  engineering team. This   is more than   a hands-on   development role. We're   looking for someone   who will elevate   the team's engineering   practices, mentor fellow   engineers, drive technical   excellence, and lead   by example in   building reliable, scalable, and maintainable software. You'll work on   a mission-critical   enterprise platform responsible   for managing the   complete lifecycle of   product pricing across   100+ global markets . The platform powers   everything from product   catalog ingestion and   cost modeling to   pricing calculations and   the distribution of   finalized pricing data   to downstream commerce   and finance systems. Our technology stack   includes a modern   React   frontend, multiple   Spring Boot   microservices supporting   REST APIs, event-driven integrations, and   batch processing, shared   domain libraries, and   cloud-native infrastructure   running on   AWS   (EKS, RDS, and   S3), with integrations   across   Google BigQuery   and   Apache Kafka . We follow a   trunk-based development   model with automated   CI/CD pipelines   using   GitHub Actions ,   ArgoCD , and progressive environment   promotion from Development   through Production. Success in this   role goes well   beyond delivering features. You'll help shape   the team's engineering   culture by improving   code review quality, defining architectural   patterns, reducing technical   debt, strengthening testing   and observability practices, and helping engineers   grow through coaching, technical discussions,   and mentorship. We're   looking for someone   who raises the   bar for the   entire team—a   force multiplier rather   than an individual   contributor. AI-First Engineering AI-assisted software   development is a   core part of   how we build   software. We're looking   for an engineer   who already uses   AI coding assistants   such as   Cursor ,   Claude Code ,   GitHub Copilot ,   Kiro , or similar tools   as part of   their daily development   workflow, not as   an occasional productivity   aid, but as   an integral part   of software design, implementation, debugging, testing, documentation, and code exploration. Beyond personal productivity, you'll help the   team adopt effective   AI engineering practices   by developing reusable   prompts, project context, steering files, MCP   configurations, and team   workflows that improve   developer effectiveness   while maintaining high   standards for code   quality, security, and   engineering judgment.  Requirements 5+ years   of professional software   engineering experience,   including   3+ years in   a Senior Software   Engineer or Technical   Lead role . Expert-level proficiency   in   Java 17+ (preferably   Java 21) ,   Spring Boot ,   Spring Data JPA , and   Hibernate , with strong knowledge   of application architecture, concurrency, performance   optimization, resiliency, and error-handling   patterns. Strong frontend engineering   experience with   React ,   TypeScript , and modern state   management libraries such   as   React Query ,   Zustand , or equivalent. Able   to design scalable   frontend architectures,   not just implement   predefined requirements. Deep understanding of   relational databases, particularly   PostgreSQL , including schema design, query optimization, indexing   strategies, transaction   management, and database   migration best practices. Proven experience designing   and evolving production-grade   REST APIs , including versioning strategies, authentication and authorization, pagination, validation, error handling, backward   compatibility, and API   lifecycle management. Strong software testing   mindset with hands-on experience implementing   unit, integration, contract, and end-to-end tests , while advocating for   maintainable, testable   architectures and quality   gates within CI/CD pipelines. Solid experience with   modern development workflows, including   Git , trunk-based development, pull request reviews, automated CI/CD   pipelines, static analysis, and code quality   enforcement. Working knowledge of   cloud-native applications   and infrastructure, including   AWS   (EKS/Kubernetes, RDS, S3) or equivalent   cloud platforms, with   an understanding of   containerization, deployment   strategies, scalability, networking, and observability. Experience building and   supporting distributed   systems, asynchronous messaging, and event-driven   architectures (Kafka or   equivalent) is highly   desirable. Nice to Have Experience building large-scale batch processing   or ETL pipelines   using   Spring Batch   or similar frameworks. Experience with   Apache Kafka   and event-driven   architectures, including   producer/consumer patterns, retries, dead-letter   queues (DLQs), and   message reliability. Experience developing enterprise   applications that manage   large datasets using   components such as   AG Grid   or equivalent data   grid libraries. Experience working with   analytical data platforms   such as   Google BigQuery   or similar cloud   data warehouses. Knowledge of   Domain-Driven Design   (DDD) , modular architectures,   shared libraries, and   reusable platform components. Experience implementing   authentication and authorization   using   Microsoft Entra ID ,   MSAL , OAuth2/OIDC, and   role-based access   control (RBAC). Experience integrating enterprise   systems such as   ERP, pricing, inventory, finance, or supply   chain platforms. Experience deploying and   operating applications   using   Kubernetes ,   GitOps , and tools such   as   ArgoCD . Familiarity with modern   Java development tools   and libraries such   as   MapStruct ,   Lombok , and annotation-based   code generation. Experience with Infrastructure   as Code using   Terraform ,   AWS CDK , or similar frameworks. Experience fostering engineering   culture through technical   communities, engineering   guilds, internal tech   talks, or mentoring   programs. Experience driving engineering   maturity by introducing   practices such as   architecture decision records   (ADRs), design reviews, observability, quality   gates, and standardized   software development processes. Hands-on experience   extending AI development   workflows through   Model Context Protocol   (MCP)   servers, custom AI   agents, developer tooling, or automation. Experience evaluating, selecting, and rolling out   AI development tools   across engineering organizations, including security assessments, governance, developer   enablement, and adoption   strategies. Contributions to open-source projects, technical   writing, conference presentations, or other forms   of knowledge sharing, particularly related to   software engineering or   AI-assisted development.