Sr. Java Engineer (Nearshore)

This engineer will join a team focused on building a strategic, machine learning-driven decision support platform designed to help business users make more informed inventory and merchandising decisions. The platform leverages machine learning outputs to generate recommendations and guide users toward the most effective next actions, such as markdowns, clearance decisions, vendor returns, and other inventory management activities. The team is responsible for developing the application layer that surfaces these recommendations through a user-friendly interface, allowing users to review and act on suggested next steps. Behind the scenes, optimization technology is used to prioritize recommendations based on business objectives, margins, and other key performance drivers. This initiative is currently in its early development phase and is not yet in production, making it an exciting opportunity to join a highly visible greenfield project from the ground up. The team will continue expanding the platform’s capabilities over time by introducing new recommendation types, increased business complexity, and additional decision-making workflows. This is a highly collaborative team of approximately seven engineers working within a modern cloud-native environment. The immediate focus will be on designing, building, and enhancing the platform rather than supporting a large portfolio of legacy applications. As the solution moves into production, team members will participate in a shared on-call rotation utilizing PagerDuty to support application health, uptime, and reliability. The ideal candidate is a strong backend engineer who enjoys building scalable distributed systems and modern microservices architectures. This role will leverage technologies including Java, Spring Boot, Kafka, AWS, Docker, and Kubernetes while working closely with engineering, product, and business stakeholders to deliver innovative, data-driven solutions.

Day-to-Day Responsibilities * Design, develop, and maintain scalable Java-based microservices and backend services. * Build and enhance RESTful APIs supporting business-critical applications. * Develop event-driven solutions leveraging Kafka and modern messaging patterns. * Partner closely with product managers, engineers, and business stakeholders to translate business requirements into technical solutions. * Contribute to architecture discussions, system design decisions, and engineering best practices. * Develop and support cloud-native applications running in AWS. * Participate in code reviews, testing, CI/CD processes, and production readiness planning. * Help scale a machine learning-driven recommendation platform from pre-production through future production phases. * Participate in a shared on-call rotation once the platform reaches production.

Core Technology Stack * Java * Spring Boot * Kafka * AWS (EC2, ECS, S3, SQS/SNS) * Kubernetes * Docker * PostgreSQL * AI-Native Development / AI-DLC

Ideal Candidate The ideal candidate is a senior-level backend engineer who combines strong Java expertise with cloud-native development experience. They are comfortable designing and building distributed systems, thrive in highly collaborative environments, and enjoy solving complex business problems through technology. Experience working with event-driven architectures, scalable microservices, and modern AWS environments will be key to success in this role. Candidates who have experience building new products from the ground up, working closely with business stakeholders, and helping shape technical direction will be especially successful on this team. The ideal individual is excited by the opportunity to contribute to an early-stage platform that combines machine learning recommendations, optimization engines, and modern cloud-native engineering practices to drive real business outcomes.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent experience. * 7+ years of professional software engineering experience. * Strong Java development expertise. * Strong Spring Framework / Spring Boot experience. * Experience building RESTful APIs and microservices. * Hands-on experience with Kafka or other event streaming platforms. * AWS cloud experience. * Experience with relational and non-relational databases. * Strong system design, architecture, scalability, and performance optimization experience. * Experience with Git version control. * Familiarity with CI/CD practices, monitoring, and alerting tools. * Experience with AI Development Life Cycle (AI-DLC). * Strong communication, collaboration, and troubleshooting skills. * Experience with Kubernetes in production environments. * Experience with Docker and containerized application development. * Experience translating complex business requirements into scalable technical solutions. * Exposure to AI-assisted development tools and modern engineering workflows. * Experience mentoring junior engineers and supporting technical growth within a team. * Experience leading design reviews and driving engineering best practices. * Strong DevOps mindset with cloud infrastructure ownership. * Experience supporting production systems and participating in on-call rotations. * New Relic. * Terraform / Infrastructure as Code. * JMeter or other performance testing tools. * Additional experience with monitoring, alerting, and observability platforms. Experience working with recommendation engines, machine learning-driven applications, or optimization-based systems.