This position sits within a fast-growing Japanese Fintech x SaaS company that builds digital tools for businesses and individuals — from accounting and finance to HR and operational automation.
The team is at the forefront of using AI and data-driven technologies to improve product efficiency and help users make smarter decisions.
As an AI Solutions Engineer, you'll be responsible for proposing, developing, and integrating AI solutions into real products used by thousands of corporate clients and individuals.
It's a highly cross-functional role where you'll collaborate with product managers, business stakeholders, and software engineers to design end-to-end systems — from idea to implementation.
Key responsibilities:
Identify business or user challenges and translate them into AI/ML use cases.
Select appropriate models or services (e.g., generative AI, NLP, data analytics) and build prototypes.
Validate model effectiveness through testing with internal teams and live data.
Design scalable, production-ready environments and deploy models to production.
Contribute to multiple AI integration projects across the company's core SaaS products.
Why this role stands out:
Direct impact:
The AI systems you build will automate complex workflows, improve decision-making, and directly contribute to business growth and customer success.
Innovation-focused: You'll work on state-of-the-art technologies including generative AI, natural language processing, predictive analytics, and big data systems.Autonomy & influence:
Engineers are given high ownership to drive ideas from concept to production within a fast-moving, small, and collaborative team.
Social impact:
The company's mission is to make work more efficient and meaningful by helping businesses digitize and automate operations.
Professional growth:
Opportunities to gain deep technical expertise, learn product strategy, and even explore global career paths across multiple regions.
Preferred background:
Hands-on experience applying AI/ML to real-world business problems (from scoping to production).
Strong software engineering foundation (Python, SQL, etc.) and familiarity with web services.
Experience using cloud platforms like AWS, GCP, or Azure.
Basic data analytics, statistics, and visualization skills.
Business-level Japanese and English required for communication with stakeholders and cross-functional teams.
Tech stack snapshot:
ML & AI:
Python, TensorFlow, Keras, AWS SageMaker, GCP BigQuery
Backend:
Go, Rails
Frontend:
React, Vue, TypeScript
Infra & Tools:
Docker, Terraform, GitHub Actions, CircleCI, Datadog, Jira, Slack
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