Job Title: AI Software Engineer (MVP Development) 
Location: Bengaluru 
Experience: 3-6 years 

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 

This job description is not exhaustive and may be subject to change. The successful candidate will be a highly motivated and skilled individual with a passion for software development and a commitment to delivering high-quality results.