Forward Deployed Engineer ( AI)
- Compensation
- Not disclosed
- Location
- Ojima
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Solutions engineering
- Posted
Skills
Must have
- Minimum 8 years of experience in software engineering, technical implementation, or related technical delivery roles
- Proven experience driving projects with direct client engagement and stakeholder management
- Experience working in fast-paced, ambiguous delivery environments with strong ownership and execution capability
Nice to have
- Business-level or higher Japanese language proficiency
- Experience implementing large-scale enterprise systems
- Experience in data security, governance, and access control design
- Experience working in startup or new business environments
- Experience collaborating with global or distributed teams
- Strong English communication skills
- Experience with observability tools and operational monitoring for AI systems
Full description
Job Description: Forward Deployed Engineer (FDE)
Overview:
The Forward Deployed Engineer (FDE) is responsible for designing,
building, and deploying AI-powered applications in close collaboration with
customers, bridging the gap between business problems and production-ready
technical solutions. This role combines hands-on software engineering, applied
AI implementation, and direct customer engagement, ensuring that solutions are
technically robust, operationally scalable, and aligned with business outcomes.
The FDE works at the intersection
of application engineering, AI systems, data workflows, and customer delivery,
partnering directly with client stakeholders, product teams, and internal
engineering teams to rapidly translate requirements into working solutions. The
role requires strong technical depth in modern application development,
cloud-native systems, and Generative AI implementation, along with the ability
to operate effectively in ambiguous and fast-moving delivery environments.
Roles & Responsibilities:
- Engage directly with customers to understand
business challenges, technical requirements, and operational constraints
- Translate customer requirements into solution
designs, technical workflows, and implementation plans
- Design, develop, and deploy production-grade
applications using Python, JavaScript, or related technologies
- Build and integrate LLM-powered applications,
including conversational systems, automation workflows, and
knowledge-based systems
- Design and implement Retrieval-Augmented
Generation (RAG) pipelines, including document ingestion, embedding
strategies, retrieval optimization, and response orchestration
- Build and manage agent-based architectures,
including task orchestration, tool integration, and execution flows
- Design and maintain evaluation frameworks to
measure model quality, retrieval effectiveness, and output reliability
- Implement and manage MLOps/LLMOps pipelines
covering deployment, monitoring, versioning, rollback, and lifecycle
management
- Develop and deploy applications in cloud