AI Software Development Engineer (AI SDE3)

Overview:

The AI Software Development Engineer – Level 3 (AI SDE3) is responsible for independently designing, building, and optimizing AI-enabled application components across frontend, backend, and data workflows. This role combines strong software engineering capability with applied AI implementation expertise, contributing to architectural decisions, solving complex technical problems, and guiding implementation quality across the engineering team.

The AI SDE3 works closely with Technical Leads, Forward Deployed Engineers, Business Architects, and Technical Program Managers to translate business and technical requirements into scalable, production-ready software solutions. The role is expected to operate with high ownership, drive technical problem-solving independently, and contribute to system architecture, AI workflow design, and engineering best practices.

Responsibilities:

Design and implement complex application features across frontend, backend, and AI workflow layers

Independently develop and maintain backend services and APIs using Python and FastAPI

Build frontend interfaces and interaction layers using React, Next.js/Remix, and Tailwind CSS

Implement real-time streaming workflows using Server-Sent Events (SSE) or similar technologies

Design and implement LLM-integrated applications, including business workflow automation and knowledge retrieval systems

Build and optimize Retrieval-Augmented Generation (RAG) pipelines, including advanced retrieval strategies, hybrid search, and re-ranking techniques

Develop and maintain evaluation loops to measure AI output quality, retrieval effectiveness, and guardrail compliance

Design and implement guardrails and control mechanisms to improve safety, reliability, and output consistency

Contribute to architecture decisions related to service decomposition, integration patterns, and scalability

Build and optimize data pipelines, data transformation workflows, and data quality validation mechanisms

Implement and optimize CI/CD pipelines, deployment automation, and infrastructure provisioning workflows

Ensure systems meet security requirements, including authentication, authorization, and access control enforcement

Implement observability standards including logging, monitoring, tracing, and alerting

Review code, mentor junior engineers, and enforce engineering quality standards

Translate business and product requirements into technical specifications and implementation plans

Troubleshoot complex issues across application, AI, and infrastructure layers

Requirements:

Experience

4 to 6 years of software development experience

Experience building production-grade software systems, including exposure to AI-enabled or data-driven systems

Proven ability to independently own features and contribute to architectural decisions

Architecture & System Design

Strong understanding of microservices architecture patterns and service decomposition

Experience implementing Test Driven Development (TDD) and structured testing practices

Strong understanding of database design principles across SQL and NoSQL systems

Ability to design scalable, maintainable, and resilient application components

Frontend Development

Strong experience in React development

Experience building responsive interfaces using Tailwind CSS

Familiarity with Next.js or Remix frameworks

Understanding of SSE (Server-Sent Events) for real-time communication and streaming interactions

Backend Development

Strong hands-on experience with Python development

Strong expertise in FastAPI and modern API development practices

Strong understanding of REST API principles, service integration, and backend architecture

Experience building scalable backend workflows and asynchronous processing patterns

AI / ML Engineering

Strong understanding of LLM integration patterns and AI application workflows

Hands-on experience implementing advanced RAG architectures

Experience with Hybrid Search and Re-ranking strategies for retrieval optimization

Experience designing and maintaining evaluation loops for model quality and response consistency

Experience implementing Guardrails for safe and reliable AI behavior

Data Engineering

Experience in data exploration and profiling

Experience building and maintaining data pipelines

Understanding of data quality validation and data integrity practices

Familiarity with structured and semi-structured data handling patterns

DevOps & Cloud Engineering

Strong working knowledge of Docker and Kubernetes

Experience implementing and maintaining CI/CD pipelines

Hands-on experience with Infrastructure-as-Code (Terraform)

Understanding of cloud-native deployment patterns and release management

Security & Observability

Strong understanding of IAM, OAuth2, and secure API design

Familiarity with network policies and service security controls

Experience implementing monitoring and observability using Prometheus, Grafana, and OpenTelemetry

Engineering Practices

Strong debugging and troubleshooting capability across application and AI layers

Strong understanding of testing strategies and engineering quality practices

Experience in collaborative development and version control workflows

Ability to document technical decisions, designs, and implementation patterns clearly

Soft Skills

Strong ownership and accountability for delivery outcomes

Ability to communicate technical trade-offs and architecture decisions clearly

Strong collaboration and adaptability in cross-functional teams

Leadership capability in guiding junior engineers and supporting team delivery

Strong problem-solving mindset with structured scenario analysis

Ability to translate business requirements into technical implementation plans

Reliability mindset with focus on system stability and maintainability

Openness to feedback and continuous improvement

Nice to Have

Experience with LLM orchestration frameworks such as LangChain or similar

Exposure to vector databases and semantic search systems

Experience working with cloud platforms (AWS, Azure, GCP)

Experience in AI-first product or platform engineering environments

Experience supporting enterprise-scale AI implementations

Japanese language proficiency preferred for client-facing or Japan-based roles

Language Requirements

English: Working proficiency required

Japanese: Desirable