Job
Description
You are a highly skilled and motivated AI Tech Lead sought by Rakuten, a global internet service company offering a wide range of services to approximately 1.4 billion customers worldwide. Your primary responsibility will be to develop and scale next-generation AI-driven platforms, particularly e-commerce catalog systems, by integrating cutting-edge AI technologies such as Large Language Models (LLMs). To excel in this role, you should possess a strong background in backend engineering, Artificial Intelligence (AI), Data Science, and Machine Learning (ML), with a focus on designing, developing, and deploying end-to-end ML pipelines and AI-driven solutions. This position requires a combination of technical leadership, backend development, and AI/ML expertise to create data-intensive solutions for various business use cases. As the AI Tech Lead, your key responsibilities will include: Leading the design, development, and deployment of scalable, production-grade platforms for AI-driven applications, particularly e-commerce catalog operations. Defining architectural standards for backend systems to ensure scalability, fault tolerance, and maintainability. Providing mentorship to the engineering team to foster technical excellence and best practices. Driving cross-functional collaboration to align technical solutions with business objectives. Designing and implementing solutions utilizing Large Language Models (LLMs) such as OpenAI GPT APIs, LLAMA2/LLAMA3, or similar frameworks. Fine-tuning and optimizing LLMs for performance, accuracy, and relevance in applications like conversational AI, catalog optimization, and personalization. Building and maintaining Retrieval-Augmented Generation (RAG) systems and vectorized databases for enhanced AI capabilities. Collaborating with data science teams to deploy AI/ML models for predictive analytics, intent classification, Named Entity Recognition (NER), and other NLP tasks. Developing and maintaining robust backend systems using Java, Python, and frameworks like Spring Boot, FastAPI, Django, and Flask. Creating APIs and microservices to handle high volumes of data in real-time with low latency. Optimizing platform performance to support large-scale catalogs and global user traffic. Ensuring high availability and fault tolerance for critical operations. Working with data engineers to design and optimize data pipelines, ensuring the availability and quality of training datasets. Developing scalable systems to process and store large volumes of data using big data technologies like Hadoop, Spark, or Kafka. Leveraging advanced tools like MLflow, Prefect, and AWS Sagemaker for efficient model training, deployment, and monitoring. Deploying and managing backend services and ML models on cloud platforms like AWS, GCP, or Azure. Setting up and optimizing CI/CD pipelines for seamless deployments and updates. Monitoring system and model performance to ensure smooth operations and rapid troubleshooting. Utilizing containerization tools like Docker and Kubernetes for scalable deployments. Partnering with product management, business development, and engineering teams to define platform requirements and AI/ML solutions. Communicating complex technical concepts to non-technical stakeholders effectively. Staying updated on industry trends in AI, ML, and backend development to drive innovation. To qualify for this role, you should have: Minimum 8 years of experience in backend development, with expertise in Java, Python, Spring Boot, microservices, and RESTful APIs. Experience in designing and scaling production-grade platforms for high-volume applications. Proficiency in integrating LLMs like OpenAI GPT, LLAMA2/LLAMA3, and frameworks such as Hugging Face Transformers. Hands-on experience with TensorFlow, PyTorch, or similar tools. Strong knowledge of big data technologies like Hadoop, Spark, or Kafka. Familiarity with RAG systems, vectorized databases, and retrieval-based AI. Proven experience with cloud platforms (AWS, Azure, GCP) and containerization tools like Docker and Kubernetes. Expertise in CI/CD pipelines and system monitoring.,
