Lead Java/Kotlin/AI Engineer

About the Position

N-iX is looking for a Lead Java/Kotlin/AI Engineer to join the team of our client, a global e-commerce leader headquartered in California. This is a high-impact individual contributor role focused on shaping, building, and scaling advanced AI systems at one of the world’s most established and heavily trafficked ecommerce platforms.

Responsibilities

• 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 that span multiple services, systems, teams, or product surfaces.
• Design and build agent-led user experiences and backend systems that leverage task decomposition, memory, tool use, dynamic planning, retrieval, workflow orchestration, and multi-agent coordination.
• Translate ambiguous business, research, and product opportunities into clear technical strategies, architecture proposals, implementation plans, milestones, risks, and tradeoffs.
• Drive architectural decisions for AI-powered products and platforms, ensuring systems are reliable, maintainable, scalable, cost-effective, observable, and production-ready.
• 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.
• Help 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.

Requirements

• 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 that serve 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, or other service/API patterns, Production monitoring, observability, alerting, incident response, and 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, including LLM-based agents, autonomous workflows, task-planning systems, tool-using agents, retrieval-augmented agents, or multi-agent orchestration.
• Strong understanding of Generative AI system design, including prompt orchestration, model integration, retrieval, grounding, tool use, evaluation, guardrails, observability, and production monitoring.
• Experience with retrieval-augmented generation, vector databases, embeddings, semantic search, ranking, knowledge-grounded AI, or information retrieval systems.
• Knowledge of tool-use frameworks, agent orchestration platforms, AI workflow automation, multi-modal model integration, or multi-agent system design.
• Experience building internal AI platforms, developer tools, reusable AI services, model-serving infrastructure, evaluation platforms, or shared ML infrastructure.
• Experience operating AI systems in high-traffic ecommerce, marketplace, search, personalization, recommendations, ads, trust, risk, payments, or customer-service environments.
• Experience defining responsible AI practices, model governance processes, safety evaluation, abuse-prevention patterns, or production AI monitoring standards.
• Experience with streaming data systems such as Kafka.

We Offer

• Flexible working format - remote, office-based or flexible.
• A competitive salary and good compensation package.
• Personalized career growth.
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more).
• Active tech communities with regular knowledge sharing.
• Education reimbursement.
• Memorable anniversary presents.
• Corporate events and team buildings.
• Other location-specific benefits.

not applicable for freelancers