Software Engineer

Role Purpose

We are seeking a highly autonomous and result-driven AI Software Engineer to transform cutting-edge research from Fujitsu LAB into production-ready Minimum Viable Products (MVPs). This role requires a versatile engineer who can independently drive the entire software development lifecycle—from understanding high-level product requirements to implementing robust, scalable AI solutions across cloud infrastructure.

The ideal candidate thrives in fast-paced environments with short engineering cycles, can translate abstract requirements into actionable engineering tasks, and has a proven track record of delivering AI/ML products across diverse domains with minimal supervision. The ideal candidate should also be comfortable in working with non-AI products related to computing, security and quantum software.

Key Responsibilities

AI/ML Product Development

• Transform Fujitsu LAB research prototypes and algorithms into production-grade MVPs
• Design, develop, and deploy end-to-end AI/ML applications and services
• Implement and optimize Large Language Models (LLMs) and machine learning pipelines for real-world applications
• Work with advanced AI concepts such as Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering.
• Evaluate and test AI models using theoretical ML knowledge and practical frameworks.
• Create scalable data processing pipelines for AI model training and inference

Full-Stack Development

• Build robust backend services using Python and C++ for high-performance AI workloads
• Develop responsive frontend interfaces using React and JavaScript
• Design and implement RESTful APIs and microservices architectures
• Integrate AI models with web applications and cloud services

Cloud Infrastructure & DevOps

• Architect and deploy cloud-based systems using AWS CloudFormation or similar tools.
• Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring
• Implement DevOps best practices and QA automation frameworks
• Manage containerized applications using Docker and orchestration tools
• Optimize cloud resource utilization and cost efficiency

System Architecture & Security

• Design secure system architectures with proper authentication, authorization, and data protection
• Implement encryption, secure API design, and vulnerability management.
• Ensure system reliability through logging, monitoring, and disaster recovery strategies.

Project Management & Collaboration

• Collaborate with product managers, researchers, and cross-functional teams.
• Participate in Agile ceremonies and contribute to sprint planning and retrospectives.
• Mentor junior engineers and foster a culture of knowledge sharing.
• Conduct code reviews and promote best practices across the team.

Version Control & Software Lifecycle

• Manage source code using GitHub/GitLab with proper branching strategies
• Implement semantic versioning and release management practices
• Maintain clean commit history and meaningful pull requests
• Track issues, features, and technical debt systematically

Required Qualifications

Education & Experience

• Bachelor's or Master's degree in Computer Science, Software Engineering, AI/ML, or related field
• 3-5 years of professional software development experience
• Must have: Completed at least one production deployment of an LLM or machine learning model project

Technical Skills (Must Have)

• Strong programming proficiency in:
• Python (for AI/ML development, backend services)
• C++ (for performance-critical components)
• JavaScript/React (for frontend development)
• Proven experience with:
• LLM integration and deployment (Hugging Face, open-source models, LLM APIs, etc.)
• Machine learning frameworks (PyTorch, vLLM, scikit-learn)
• Cloud platforms, specifically AWS services
• GitHub/GitLab workflows and Git version control
• CI/CD pipeline design and implementation (GitLab CI, GitHub Actions)
• DevOps practices and QA automation

Experience Requirements

• Participated in multiple large-scale product projects across different domains
• Deep understanding of complete software product lifecycle (planning, development, testing, deployment, maintenance)
• Track record of shipping production AI/ML applications

Essential Soft Skills

• High autonomy: Able to execute complex engineering tasks with minimal technical guidance
• Rapid adaptability: Thrives in fast-paced environments with short development cycles
• Requirement translation: Can independently convert high-level business requirements into detailed technical specifications
• Self-motivated: Strong sense of ownership and accountability
• Problem-solving: Excellent analytical and debugging skills
• Strong communication skills for technical and non-technical audiences

Preferred Qualifications

Additional Technical Skills

• Experience with MLOps tools (MLflow, DVC), model serving (FastAPI, TorchServe).
• Knowledge of confidential computing, TEE, and AI security.
• Understanding of hardware acceleration (GPU, TPU).
• Familiarity with performance profiling and A/B testing frameworks.
• Experience with distributed systems and microservices architecture