Solutions Architect Graduate

Team Introduction Join the Innovative BytePlus Team! As part of BytePlus, you will help enterprises and AI-native developers build the next generation of their businesses. By leveraging ByteDance’s cutting-edge technologies in AI models, agent solutions, and cloud infrastructure, we are committed to developing innovative products and solutions that shape the future. We enable our clients to focus on what matters most, and you can play a key role in helping us achieve that mission. In Japan, we partner with leading enterprises across a wide range of industries to drive AI adoption from proof of concept (PoC) to scalable commercial deployment. Our goal is not only to showcase advanced technology, but also to help organizations create sustainable, measurable business value. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities Pre-Sales & Solution Design - Partner closely with the Japan regional Sales team to identify customer business challenges and technical requirements. - Break down complex business problems into practical and scalable AI solutions. - Lead technical demos, architecture discussions, RFI/RFP responses, and PoC design and delivery. - Drive PoC-to-production conversion and ensure measurable business impact. - Build technical credibility within customer organizations, from engineering teams to C-level executives. AI Solution Development & Optimization (Hands-on) - Participate in or lead the design and implementation of Generative AI applications, including LLMs, RAG systems, agent architectures, and multimodal solutions. - Design and implement end-to-end system architectures, including model orchestration, knowledge base construction, vector database integration, API connectivity, and overall system integration. - Evaluate system performance in real production environments (accuracy, latency, cost, scalability). - Optimize prompt structures, inference workflows, and caching strategies to improve system stability and efficiency. - Continuously refine solutions based on customer business KPIs. Commercial Collaboration & Project Execution - Act as the technical lead in customer engagements, supporting commercial discussions and technical negotiations. - Collaborate with the Sales team to drive deal closure and contract execution - Support account expansion initiatives (upsell / cross-sell). - Take ownership of both technical quality and commercial success of assigned projects. - Build and maintain long-term trusted relationships with enterprise clients. Product & Market Feedback Bridge - Provide structured frontline feedback to Product and Engineering teams. - Drive localization and optimization of products for the Japan market. - Identify repeatable, industry-level AI solution patterns and support scalable adoption. - Contribute to the development of industry solution frameworks and methodologies for Japan. Minimum Qualification(s) - Individuals who are completing or have recently completed a Bachelor's / Master's degree in Artificial Intelligence, Computer Science, Engineering, Mathematics, Software Engineering, or a related technical discipline. - Strong software engineering fundamentals, with proficiency in Python preferred, and the ability to build and integrate applications through academic, internship, or personal projects. - Familiarity with Generative AI technologies, such as LLMs, RAG architectures, agent systems, or multimodal models. - Exposure to deploying applications in cloud or containerized environments, such as Docker, Kubernetes, or major public cloud platforms. Preferred Qualification(s) - Understanding of Transformer architecture fundamentals and prompt engineering principles. - Exposure to knowledge base systems and vector databases through coursework, internships, research, or personal projects. - Familiarity with common agent or AI application frameworks such as LangChain or LlamaIndex. - Understanding of inference optimization, latency considerations, and cost-efficiency in AI applications. - Interest in designing end-to-end AI systems with scalability and production readiness in mind. - Hands-on experience applying Generative AI or multimodal models through academic projects, internships, hackathons, competitions, or research. - Ability to connect technical solutions with practical use cases and business impact. - Strong learning agility, problem-solving skills, and the ability to work effectively in a cross-functional environment. - Good communication skills, with the ability to explain technical ideas clearly to both technical and non-technical stakeholders.