java developer in ecommerce

N-iX’s client is a global e-commerce leader headquartered in California that connects millions of buyers and sellers across more than 190 markets. The role focuses on building and scaling advanced AI systems for a major ecommerce platform.

• Lead the architecture, design, development, and optimization of scalable AI systems using Generative AI, LLMs, retrieval-augmented generation, and agent-based architectures;
• Serve as the technical owner or technical lead for high-impact AI initiatives spanning multiple services, systems, teams, or product surfaces;
• Design and build agent-led user experiences and backend systems with task decomposition, memory, tool use, dynamic planning, retrieval, workflow orchestration, and multi-agent coordination;
• Translate ambiguous business, research, and product opportunities into technical strategies, architecture proposals, implementation plans, milestones, risks, and tradeoffs;
• Drive architectural decisions for reliable, maintainable, scalable, cost-effective, observable, and production-ready AI products and platforms;
• Contribute directly to complex implementation work across backend services, AI orchestration layers, model integration systems, evaluation frameworks, APIs, data pipelines, and observability tooling;
• Partner with Product, Research, Data Engineering, Platform Engineering, and Software Engineering teams to align AI system design with user needs, business goals, platform capabilities, and operational constraints;
• Establish and promote technical standards for AI system design, agent architecture, LLM integration, evaluation, experimentation, responsible AI, production monitoring, and operational excellence;
• Lead design reviews, architecture reviews, code reviews, technical planning sessions, and production-readiness reviews for complex AI systems;
• Mentor and guide engineers through technical problem solving, design feedback, implementation support, code quality improvements, and knowledge sharing;
• Advance the internal GenAI platform by contributing reusable components, APIs, frameworks, reference architectures, evaluation patterns, engineering guidelines, and shared services;
• Define and improve AI evaluation practices, including offline evaluation, online experimentation, regression testing, model behavior analysis, quality measurement, human feedback loops, and production feedback mechanisms;
• Monitor and optimize AI systems in production for latency, quality, scalability, reliability, availability, cost efficiency, safety, and responsible AI use;
• Identify technical risks early and drive practical mitigation plans across architecture, implementation, launch, and operations;
• Influence technical strategy across teams by aligning engineering decisions with broader organizational goals, platform direction, and long-term scalability;
• Stay ahead of advances in AI, LLMs, machine learning engineering, AI agents, retrieval systems, model serving, evaluation tooling, and emerging developer frameworks, applying a pragmatic lens to production adoption;
• Drive continuous improvement across design, implementation, evaluation, deployment, monitoring, incident response, and operational processes.

• 10+ Years of experience in software engineering, machine learning engineering, AI engineering, distributed systems, or related technical roles;
• 3+ Years of experience leading complex technical initiatives, setting architecture, mentoring engineers, or providing technical direction across teams;
• Deep hands-on engineering skills with the ability to personally design and implement complex production systems;
• Strong programming skills in Java, Kotlin, or similar JVM languages;
• Experience designing and operating production-grade AI systems, distributed services, APIs, or platform components serving high-volume, real-world user traffic;
• Ability to lead technical discussions, evaluate tradeoffs, influence senior partners, and communicate complex AI concepts clearly to technical and non-technical collaborators;
• Hands-on experience with Spring Framework, Reactive Programming, Docker and Kubernetes, distributed systems and scalable backend services, REST, GraphQL, gRPC, production monitoring, observability, alerting, incident response, performance optimization, CI/CD, automated testing, deployment practices, and operational support;
• Excellent English communication skills;
• Nice to have: Hands-on experience building agent-led systems, Generative AI system design, retrieval-augmented generation, vector databases, embeddings, semantic search, ranking, knowledge-grounded AI, information retrieval systems, tool-use frameworks, agent orchestration platforms, AI workflow automation, multi-modal model integration, multi-agent system design, internal AI platforms, developer tools, reusable AI services, model-serving infrastructure, evaluation platforms, shared ML infrastructure, high-traffic ecommerce or related environments, responsible AI practices, model governance, safety evaluation, abuse-prevention patterns, production AI monitoring standards, Kafka.

• Remote work is available across the European Union.