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★Software Engineer (Data Platform) | AI/NLP Company Business Level Japanese Required (N2 Level) ◆ Flextime System & Fully Remote Work ◆ In-house Products ◆ 123 days off per year ◆ Annual salary: 6.5 million yen - 11 million yen -------------【About the company】------------- The company's mission is "to advance humanity by reinventing the mechanisms of value creation" and aims to create an environment where people can focus on creating new value through the use of natural language processing and AI technologies. AI delivers information directly related to business operations, thereby enhancing the information sensitivity of the organization. In addition, the company offers two SaaS products: "Anews," which encourages the conception of business ideas and their development within the organization, and "Astrategy," a market research service that provides suggestions by structuring necessary information according to the organization and its operations. Currently, its main target is major manufacturing R&D in Japan, and more than 30% of the Nikkei 225 companies have already adopted the system. In the future, starting with manufacturing R&D, the company plans to expand to domestic enterprise companies, then to Japanese companies as a whole, and even to global companies. The company completed a Series C financing of 1.1 billion in August 2022. In February 2024, they were selected for the "GENIAC (Generative AI Accelerator Challenge) Project" promoted by the Ministry of Economy, Trade and Industry and NEDO, and have begun to develop their own LLM with 100 billion parameters! The company has grown to 100 employees and is looking for more personnel to achieve further growth! -------------【 Job Description】------------- 【Company Overview】 The company leverages cutting-edge Generative AI and Large Language Model (LLM) technology to drive corporate transformation. It operates a SaaS business featuring an AI agent tailored for engineers in the manufacturing sector, alongside a new PaaS business—a platform designed to structure fragmented internal data and transform it into valuable corporate assets. Currently, the primary market focus is R&D departments within major Japanese manufacturing firms. The company’s solutions have already been adopted by over 300 organizations, representing 30% of the Nikkei 225. Looking ahead, the company plans to expand from manufacturing R&D into the broader domestic enterprise market, eventually scaling to all Japanese industries and global corporations. Furthermore, the company is deeply invested in the research and development of purely domestic LLMs with high proficiency in the Japanese language and business domains. In May 2024, it released a proprietary LLM featuring 100 billion parameters. Following a Series D funding round in October 2024, which raised 4.5 billion JPY (bringing the cumulative total to 8.8 billion JPY), the workforce has grown to approximately 150 employees. The company is now actively recruiting to fuel its next phase of hyper-growth. 【Current Challenges】 ・Lack of specialized talent to architect, construct, and maintain large-scale data pipelines responsible for crawling, content extraction, and high-throughput distribution across hundreds of millions of web-based documents. ・Shortage of technical leads capable of proactively planning data enrichment strategies, defining technical requirements, and executing implementation for in-house AI Agent development, while collaborating seamlessly with product managers and cross-functional engineering teams. 【Your Role】 The company provides multiple products leveraging cutting-edge Generative AI to empower enterprise decision-making and business transformation. These platforms rely on collecting and structuring vast amounts of public information relevant to corporate activities, including news, patents, academic literature, and web data. In this position, you will own the end-to-end design, development, and operation of the web crawler and document distribution pipeline, which serves as the core data distribution engine underlying all company products. As a foundational data platform that directly underpins core product value, this role demands systems engineering focused heavily on stability, scalability, and extensibility. Alongside hands-on engineering to address key data infrastructure challenges, you are expected to lead the Data Platform Team and drive efforts to maximize overall engineering productivity. ■Responsibilities ・Design, build, and operate data platforms using TypeScript and Python to distribute high-volume web news, patent data, academic papers, and enterprise-relevant content. ・Enhance distributed processing scalability and build robust monitoring/observability architectures within serverless environments. *Scope of Reassignment: Development-related operations. 【Team Structure】 Business Head (CEO): 1 Engineering Manager / Head of Development: 1 Product Engineers: 7 AI Agent Engineers: 6 Data Structuring Engineers: 3 Data Engineers: 3 Product Manager (PdM): 1 Researcher: 1 Customer Success (CS): 2 Business Development / Sales (Biz): 8 【Development Environment】 [Programming Languages] Data Pipeline: Python Web Crawler: TypeScript (Node.js) [Containers] Docker [IaC] Terraform [Cloud] AWS [Libraries] Pyspark, Puppeteer [AI Tools] Cursor, CodeRabbit, Devin 【Position Highlights】 By contributing to the development and operation of the unified document distribution system powering all products, you will gain the following high-impact experience: ・Hands-on experience designing, building, and operating serverless distributed architectures handling massive dataset scales reaching hundreds of millions of document records. ・Insights into developing web crawlers targeting tens of thousands of websites, leveraging both front-end and back-end expertise while mastering monitoring and operational strategy designed for inherently unpredictable external environments. ・Direct business impact by collaborating closely with Product Managers and Customer Success teams to proactively drive feature development, architectural improvements, and strategic initiatives grounded in client needs and product requirements. -------------【 Requirements】------------- 【Required】 *Meet all of the following ・3+ years of experience as an engineer ・Experience developing applications using Python ・End-to-end experience spanning requirements definition, design, implementation, and operations *Meet any of the following ・Experience in full-stack development and operations using serverless technologies, as well as experience leading such efforts (Lambda, ECS, Fargate, Step Functions, etc.) ・Experience in building data pipelines and ETL processes, as well as in development and operations using workflow engines and distributed processing frameworks (such as Spark) 【Preferred】 ・Master’s or doctoral degree in a technology field related to computer science ・Experience leading team-based development ・Experience developing and operating in-house services for customers ・Experience developing and operating services for document search and recommendation ・Broad knowledge of and practical experience with serverless computing ・Experience in development and operations using Terraform 【Ideal Applicants】 ・Deep passion for computer science and distributed systems architecture. ・Driven to follow, evaluate, and benchmark cutting-edge theoretical concepts and industry best practices. ・Able to go beyond given assignments by formulating key questions independently and engineering necessary solutions. ・Skilled at collaborating with business stakeholders to maximize technical impact on product outcomes. ・Employs a positive, growth-oriented mindset eager to tackle bold technical challenges. 【Others】 Must reside in Japan. Ability to communicate fluently in Ja
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.