AI Software Development Engineer (AI SDE2)

Overview

The AI Software Development Engineer - Level 2 (AI SDE2) is responsible for building, integrating, and supporting AI-enabled application features across frontend, backend, and cloud-native environments. This role contributes to the implementation of production-grade software components, AI-powered workflows, and platform integrations, working closely with senior engineers, Technical Leads, and Forward Deployed Engineers.

The AI SDE2 is expected to independently deliver well-defined features, contribute to debugging and system improvement efforts, and support the implementation of modern AI application patterns such as Retrieval-Augmented Generation (RAG), evaluation pipelines, and guardrail mechanisms. The role requires strong engineering fundamentals, fast learning capability, and the ability to operate effectively in fast-paced prototyping and delivery environments.

Responsibilities

• Develop and implement application features across frontend and backend systems based on defined technical designs
• Build and maintain backend services and APIs using Python and FastAPI
• Develop frontend components and user experiences using React, Next.js/Remix, and Tailwind CSS
• Implement real-time user interaction capabilities using Server-Sent Events (SSE) or similar streaming mechanisms
• Contribute to the implementation of AI-powered application features, including LLM integrations and workflow orchestration
• Support implementation of Retrieval-Augmented Generation (RAG) pipelines, including retrieval logic, ranking improvements, and response optimization
• Assist in building and maintaining evaluation loops to validate AI model output quality and reliability
• Implement and maintain guardrails and control mechanisms for safe and reliable AI behavior
• Participate in debugging, performance tuning, and issue resolution across application and AI workflows
• Contribute to API integrations and system interoperability across internal and external services
• Support containerization, deployment, and environment setup using Docker and Kubernetes
• Contribute to CI/CD pipelines and deployment automation processes
• Follow security best practices, including authentication, authorization, and secure API integration
• Maintain observability practices including logging, monitoring, and tracing
• Document implementation details, blockers, and technical decisions clearly and consistently

Requirements

Experience

• 2 to 4 years of software development experience
• Experience contributing to application development in team-based engineering environments
• Exposure to AI-enabled applications or data-driven systems preferred

Frontend Development

• Hands-on experience with React
• Experience building UI components using Tailwind CSS
• Familiarity with Next.js or Remix frameworks
• Understanding of Server-Sent Events (SSE) or similar real-time communication mechanisms

Backend Development

• Strong hands-on experience in Python development
• Experience building backend APIs using FastAPI
• Strong understanding of REST API principles, API design, and integration patterns
• Understanding of backend performance optimization and debugging practices

AI / ML Engineering

• Working knowledge of Large Language Model (LLM) integration concepts
• Experience or exposure to Retrieval-Augmented Generation (RAG) implementation
• Understanding of advanced retrieval concepts including Hybrid Search and Re-ranking
• Familiarity with evaluation loops and model quality validation
• Understanding of guardrails and AI safety mechanisms

DevOps & Platform Engineering

• Working knowledge of Docker and Kubernetes
• Understanding of CI/CD pipelines and deployment workflows
• Familiarity with Infrastructure-as-Code (Terraform)
• Basic understanding of cloud-native deployment principles

Security & Observability

• Understanding of IAM, OAuth2, and secure authentication flows
• Familiarity with API security and access control patterns
• Basic experience with Prometheus, Grafana, and OpenTelemetry for monitoring and tracing

Engineering Practices

• Strong understanding of software development fundamentals, debugging, and testing practices
• Ability to follow coding standards, documentation practices, and engineering processes
• Understanding of version control workflows and collaborative development practices

Soft Skills

• Strong team collaboration and cross-functional communication skills
• Ability to communicate blockers, risks, and progress clearly
• Learning agility and willingness to quickly adopt new tools and frameworks
• Ability to work effectively in fast-paced prototyping and delivery environments
• Strong ownership mindset for assigned deliverables and system stability
• Problem-solving mindset with strong analytical thinking and scenario evaluation
• Discipline in documentation and technical communication

Nice to Have

• Experience with LLM application frameworks such as LangChain or similar orchestration frameworks
• Exposure to vector databases and semantic search systems
• Experience working on AI-first or GenAI product development
• Exposure to cloud platforms such as AWS, Azure, or GCP
• Experience working in multicultural or distributed teams
• Japanese language proficiency preferred for customer-facing or Japan-based roles

Language Requirements

• English: Working proficiency required
• Japanese: Working proficiency required