Take Generative AI Beyond the Prototype and Into Production
Generative AI is changing how businesses operate, but building an impressive prototype is only the beginning.
The real challenge is turning that technology into reliable, secure, production-ready systems that solve business problems at scale.
We're working with an AI-focused technology joint venture in Japan that is looking for a Software Deployment Engineer (SDE) to help some of the country's largest enterprises implement advanced AI solutions.
In this role, you'll work directly with enterprise customers to build and deploy LLM-powered applications, AI agents, Retrieval-Augmented Generation (RAG) systems, and intelligent workflow automation.
Rather than focusing on proof-of-concept projects that never make it into production, you'll take ownership of building AI solutions that become part of real business operations.
With compensation of up to ¥20 million annually, a flexible hybrid working environment, and opportunities to collaborate with leading AI researchers and engineers, this position offers a chance to work at the forefront of enterprise AI adoption in Japan.
Position Overview
| Category | Details |
|---|---|
| Position | Software Deployment Engineer (SDE) |
| Industry | Generative AI / Enterprise Technology |
| Location | Hamamatsucho, Tokyo |
| Salary | ¥7.6M–¥20M annually (including bonus) |
| Work Style | Hybrid / Super-flex (no core hours) |
| Experience | 3+ years of software engineering experience |
| Languages | Business-level Japanese or higher |
| Technical Focus | Python, JavaScript, LLMs, RAG, AI Agents, Cloud Infrastructure |
| Travel | Customer visits, domestic business trips, potential travel to San Francisco |
| Career Development | Potential progression toward Forward Deployed Engineer (FDE) |
About the Company
Our client is an AI-focused technology joint venture working to accelerate the adoption of advanced artificial intelligence across Japan's enterprise sector.
Its mission is to help major Japanese organizations move beyond experimenting with Generative AI and begin integrating it into their everyday business operations.
By combining advanced AI technologies with the infrastructure and expertise needed to support large enterprise customers, the company is working to make AI a practical part of how businesses operate.
What makes this opportunity particularly interesting is its emphasis on real-world implementation.
Instead of developing AI demonstrations in isolation, engineers work alongside customer teams to understand business challenges, design appropriate solutions, and deliver systems that can operate reliably in production.
The engineering team also collaborates with international Product, Research, and Security specialists, providing exposure to advanced AI technologies and global engineering practices.
What Does a Software Deployment Engineer Do?
A Software Deployment Engineer is responsible for transforming AI concepts and prototypes into applications that can operate reliably in production.
While AI researchers focus on developing and improving models, deployment engineers focus on making those models useful within real business environments.
This requires a combination of software engineering, system architecture, cloud infrastructure, and practical AI application development.
You'll work closely with Forward Deployed Engineers (FDEs), who help define the broader technical scope and architecture of customer implementations.
Your responsibility will be to turn those designs into working systems, ensuring that the technology meets the customer's business, performance, security, and operational requirements.
Your Main Responsibilities
1. Build Production-Ready Generative AI Applications
You'll design and implement applications that use advanced LLMs to solve complex enterprise problems.
Your work will cover the development lifecycle, from early prototypes to production deployment, monitoring, and continuous improvement.
2. Develop AI Agents, RAG Systems, and Workflow Automation
You'll create AI-powered applications that can retrieve information, interact with enterprise data, execute workflows, and support business processes.
This may involve building RAG pipelines, designing AI agents, developing APIs, and integrating applications with existing enterprise systems.
3. Work Across the Full Technology Stack
This is a hands-on engineering role covering backend services, APIs, frontend functionality, and cloud infrastructure.
You'll need to understand how the different parts of an AI application work together and ensure the resulting system is reliable, scalable, and maintainable.
4. Collaborate Directly With Enterprise Customers
You'll work with customer engineering teams, business stakeholders, and department leaders to understand their challenges and deliver practical technical solutions.
You'll also help explain technical decisions and support customers as they adopt new AI capabilities.
5. Evaluate and Continuously Improve AI Performance
Deploying an AI system is not the end of the project.
You'll develop evaluation processes, analyze model outputs, improve prompts and application behavior, and establish feedback loops that support continuous quality improvements.
6. Build Reusable Solutions
As successful implementations emerge, you'll help turn them into reusable technical assets, templates, and deployment patterns.
These solutions can then support future customer projects, accelerating enterprise AI adoption.
Tech Stack and Engineering Environment
This position combines traditional software engineering with modern Generative AI development.
You don't need to have experience with every technology below, but you should have a strong software engineering foundation and hands-on experience building LLM-powered applications.
| Technology / Area | Tools & Skills | How You'll Use Them |
|---|---|---|
| Programming Languages | Python, JavaScript | Building production-quality applications and services |
| Generative AI | LLMs, Generative AI APIs | Developing AI-powered enterprise applications |
| AI Application Development | RAG, AI Agents, Prompt Engineering | Building intelligent applications and automation |
| Backend Development | REST APIs, Backend Architecture | Integrating AI functionality with enterprise systems |
| Frontend Development | JavaScript, Web Application Development | Creating interfaces for AI-powered applications |
| Cloud Infrastructure | AWS, GCP, Azure | Deploying and operating cloud-based systems |
| DevOps | GitHub, CI/CD, Automation | Managing development and deployment workflows |
| Containerization | Docker | Packaging and deploying applications |
| AI Operations | Model Evaluation, MLOps, LLMOps | Monitoring, evaluating, and improving AI systems |
| Security & Governance | Data Security, Enterprise Governance | Building secure and compliant enterprise systems |
Note: This table combines required technologies with preferred skills and relevant engineering areas. Not every technology listed is mandatory.
What Skills and Experience Do You Need?
Must-Have Requirements
The company is looking for engineers with a strong foundation in software development and practical experience implementing Generative AI applications.
You should have:
3+ years of professional software engineering experience, including designing, developing, and maintaining production systems.
Experience building production-quality applications using Python, JavaScript, or similar technologies.
Hands-on experience with cloud infrastructure such as AWS, GCP, or Azure.
Practical experience designing and implementing application features powered by LLMs or Generative AI.
Experience managing development workflows using GitHub, CI/CD, DevOps practices, or automation.
The ability to contribute across the software development lifecycle, from architecture and implementation through deployment and operations.
Business-level Japanese communication skills or higher.
Nice-to-Have Skills
You'll have an advantage if you also have experience in:
RAG-based applications and AI agent development.
AI agent prototyping and experimentation.
REST API design and implementation.
Docker and automated deployment pipelines.
MLOps or LLMOps.
Enterprise-scale system implementation.
Data security, governance, or compliance.
Customer-facing technical consulting or project delivery.
Working in startups or new business environments.
Collaborating with international engineering teams.
You don't need to check every box to be considered. A strong engineering background, practical AI development experience, and the ability to solve problems independently are particularly important.
Language Requirements
Japanese: Business level or higher (required)
Because you'll work directly with Japanese enterprise customers, you'll need to communicate effectively with engineering teams, business stakeholders, and decision-makers.
This includes discussing technical requirements, explaining implementation decisions, and collaborating on solutions to complex business problems.
Salary, Working Style, and Benefits
Salary: ¥7.6M–¥20M annually (including bonus)
Compensation is determined individually based on experience, track record, and market considerations.
The stated monthly salary range is ¥537,000–¥1,414,000, including fixed overtime compensation covering 45 hours. Additional overtime payments apply when eligible employees exceed those hours, subject to employment classification.
Working Hours
The standard schedule is 9:00 AM–5:45 PM, including a one-hour break.
However, the company operates a super-flex system with no core hours, allowing employees flexibility in managing their schedules.
Location and Work Style
The office is located in Hamamatsucho, Minato-ku, Tokyo.
The position offers a hybrid working arrangement combining office and remote work. You'll also visit customer locations when necessary.
Domestic business travel is part of the role, and international travel may be possible.
Holidays and Benefits
The company provides a comprehensive benefits package, including:
Two days off per week, with 124 annual holidays in the 2025 fiscal year.
Paid annual leave and refresh leave.
Parental, childcare, and family-related leave.
Nursing and caregiving leave.
Transportation allowances.
Social insurance, including health, pension, employment, and workers' compensation coverage.
Additional leave programs and benefits are also available.
Why Consider This Opportunity?
1. Work on AI Systems That Actually Reach Production
Many Generative AI projects remain stuck in the proof-of-concept stage.
In this role, you'll focus on getting AI into real business operations.
You'll help design, deploy, and improve systems that organizations can rely on every day.
2. Work With Some of Japan's Largest Enterprises
You'll have the opportunity to solve technical challenges for major Japanese companies.
These projects may involve complex enterprise infrastructure, large datasets, demanding security requirements, and business processes that operate at significant scale.
You'll gain firsthand experience implementing AI in environments where reliability and business impact are essential.
3. Gain Exposure to Advanced AI Technologies
You'll work with advanced AI models and collaborate with specialists across Product, Research, and Security.
This provides opportunities to understand how emerging AI capabilities can be translated into enterprise-ready applications.
There's also the possibility of business travel to San Francisco, offering exposure to international AI development environments.
4. Develop Toward a Forward Deployed Engineer Career
One of the most interesting aspects of this position is its potential career progression.
As an SDE, you'll focus primarily on the implementation and deployment of technical solutions.
Over time, there's an opportunity to expand your responsibilities toward those of a Forward Deployed Engineer (FDE).
FDEs operate at the intersection of engineering, architecture, and customer problem-solving. They work closely with customers to define challenges, identify technical opportunities, and lead complex implementations.
For software engineers interested in developing stronger architectural, consulting, and leadership capabilities, this role provides a foundation for that career path.
5. Enjoy a Flexible Working Environment
The company offers a hybrid working arrangement with a super-flex schedule and no core working hours.
You'll have flexibility in how you organize your work, while also spending time collaborating in person with colleagues and customers.
The role includes customer visits and occasional business travel, primarily within Japan.
Who Would Be a Good Fit?
This opportunity could be particularly interesting for engineers who enjoy building software but also want to understand the business challenges behind the technology.
You may be a strong fit if:
You enjoy writing code and solving difficult engineering problems.
You're interested in the practical applications of Generative AI.
You want to work directly with customers instead of focusing exclusively on internal products.
You're comfortable working in environments where requirements may evolve quickly.
You can balance speed, quality, and security when delivering technical solutions.
You enjoy taking ownership and making technical decisions.
You're interested in moving toward technical architecture or Forward Deployed Engineering.
Most importantly, you should be excited about building technology that people and businesses actually use.
Frequently Asked Questions
Do I need previous experience as a Software Deployment Engineer?
No. The position requires at least three years of software engineering experience, along with hands-on experience building LLM or Generative AI applications.
You don't necessarily need to have held the SDE title previously.
Do I need experience developing or training AI models?
Not necessarily. This position focuses on implementing and deploying applications powered by existing AI models rather than training foundation models from scratch.
Experience integrating LLMs into software applications is particularly relevant.
Is this a full-stack engineering position?
Yes. The position involves working across APIs, backend systems, frontend applications, and cloud infrastructure.
While you'll have opportunities to apply your strongest technical skills, you'll benefit from being comfortable working across multiple parts of a system.
Is Japanese required?
Yes. Business-level Japanese or higher is a mandatory requirement because you'll collaborate directly with Japanese enterprise customers.
Can I work fully remotely?
The role is hybrid, combining remote work with time in the office and at customer locations. It is not advertised as a fully remote position.
Can I transition into a Forward Deployed Engineer role?
The company identifies progression toward Forward Deployed Engineering as a potential career path.
You'll work closely with FDEs and gain experience in implementation, customer engagement, and technical problem-solving that can support this progression.
What is the interview process like?
The selection process includes practical technical discussions, such as system design and case studies.
You should be prepared to explain your engineering decisions, discuss architecture, and demonstrate how you approach real-world technical problems.
What is the salary range?
The advertised annual compensation range is ¥7.6M–¥20M, including bonus.
Your final offer will depend on your skills, professional experience, and other relevant factors.
