Fujitsu - Senior AI Software Engineer

We are seeking a highly skilled and collaborative Senior AI Software Engineer to lead the development of production-grade AI/ML solutions. The role focuses on transforming advanced research into scalable, secure, and high-performance software components. The ideal candidate has strong expertise in machine learning, LLMs, intelligent agents, and applied AI engineering, combined with solid software fundamentals. The candidate should also be comfortable contributing to adjacent technology areas such as computing, security, and emerging software technologies.

Key Responsibilities :

AI/ML Model Development :

- Convert research models and prototypes into robust, deployable AI components.

- Build and optimize machine learning pipelines across deep learning, computer vision, and LLM-based systems.

- Conduct model training, fine-tuning, evaluation, and optimization for accuracy, latency, and scalability.

- Apply theoretical ML concepts to refine performance, reduce hallucinations, and improve generalization.

LLM, RAG & Intelligent Systems :

- Work with Large Language Models and integrate them into real-world applications.

- Build Retrieval-Augmented Generation (RAG) workflows using vector databases and embedding models.

- Develop intelligent agents capable of autonomous reasoning and multi-step task execution.

- Apply prompt engineering and structured prompting techniques to improve model outputs.

AI System Integration :

- Design inference architectures that ensure reliability, low latency, and production stability.

- Integrate AI models with backend systems, internal APIs, and internal development frameworks.

- Optimize GPU, CPU, and memory usage for model-serving environments.

- Collaborate with engineering teams to align AI components with broader system architecture.

Quality, Evaluation & Testing :

- Create automated evaluation frameworks to benchmark AI models against quality metrics.

- Define KPIs such as accuracy, robustness, latency, throughput, error rates, and hallucination reduction.

- Implement continuous evaluation, A/B testing, and safety validation practices.

- Maintain thorough documentation of experiments, results, and production versions.

Security, Reliability & Governance :

- Build AI components compliant with security, privacy, and data governance standards.

- Implement authentication, model-level guardrails, and data-protection mechanisms.

- Ensure fault-tolerance, monitoring, logging, and reliability at scale.

- Maintain compliance with standard security practices (e.g., OWASP, secure API design).

Required Qualifications :

- Bachelors or Masters degree in Computer Science, Engineering, AI/ML, Data Science, or related field.

- 5+ years of experience in software engineering with significant AI/ML development exposure.

- Proven experience deploying machine learning or LLM-based systems into production environments.

Technical Skills (Must Have) :

- Strong programming skills in Python, C++, and JavaScript/React.

- Hands-on experience with ML frameworks such as PyTorch, scikit-learn, TensorFlow, vLLM, etc.

- Experience integrating LLMs using Hugging Face, open-source models, and API-driven services.

- Strong understanding of embedding models, vector stores, and model-serving pipelines.

- Experience with cloud platforms (AWS preferred) for model deployment and scaling.

- Expertise in DevOps practices including CI/CD, containerization, and automated testing.

Nice-to-Have :

- Experience with model compression, quantization, pruning, or distillation.

- Exposure to GPU optimization, CUDA, or high-performance computing.

- Familiarity with multimodal AI, foundational models, or advanced transformer architectures.

- Experience working with security-centric or high-performance computing systems.

- Background in emerging technologies such as quantum computing software