Senior AI Engineer at NTT Ltd.

• The successful candidate will work across the full AI solution lifecycle—from data exploration and model development to deploying production-ready GenAI and machine learning solutions. The role requires a hands-on engineer who is comfortable working with modern AI technologies, particularly large language models (LLMs), while collaborating closely with business, engineering, and client stakeholders.

Key Responsibilities
Generative AI & Machine Learning Development

• Design and develop Generative AI solutions, including LLM-based applications
• Implement techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), and fine-tuning
• Develop and evaluate machine learning models across supervised, unsupervised, and NLP use cases
• Optimise model performance, reliability, and cost efficiency for enterprise environments

Data & Engineering Collaboration

• Work with structured and unstructured data sources (databases, APIs, documents, transcripts, logs)
• Collaborate with data engineers to support data ingestion, preparation, and transformation pipelines
• Ensure AI solutions are scalable, maintainable, and aligned with software engineering best practices

Deployment & Production

• Package and deploy AI and GenAI solutions into production (APIs, services, batch workflows)
• Support cloud-based deployments, primarily on Microsoft Azure, including Azure OpenAI and Azure AI services
• Apply MLOps and LLMOps practices such as versioning, monitoring, evaluation, and continuous improvement

Client & Stakeholder Engagement

• Translate business problems into effective AI and GenAI use cases
• Contribute to proofs of concept (POCs), pilots, and enterprise-scale implementations
• Support solution architects and senior AI leaders in client engagements and technical delivery

Qualification Requirements

• Postgraduate level qualification (Honours or Masters) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Economics or a related field
• Alternatively, equivalent practical experience delivering AI or machine learning solutions in enterprise environments

Required Skills

Core Technical Skills

• Strong proficiency in Python for AI and machine learning development
• Solid understanding of machine learning fundamentals and evaluation techniques
• Hands-on experience with ML frameworks such as scikit-learn, PyTorch, or TensorFlow
• Experience working with Generative AI and LLMs in practical use cases
• Strong data handling skills, including SQL and data querying
• Experience deploying models or AI services into production environments
• Experience with vector databases and embeddings (e.g., for RAG architectures)
• Cloud & Platforms
• Experience with cloud platforms (Azure preferred; AWS or GCP acceptable)
• Familiarity with Azure OpenAI, Azure AI services, or similar GenAI platforms
• Experience building or consuming REST APIs and using containerisation tools such as Docker
• Exposure to MLOps / LLMOps tools and practices (e.g., MLflow, monitoring, CI/CD)

Experience & Profile

• 5–10 years of experience in AI, machine learning, or applied data science roles
• Demonstrated experience delivering real-world AI or GenAI solutions beyond experimentation
• Comfortable working in a hybrid, client-facing consulting environment
• Strong communication skills and a pragmatic, delivery-oriented mindset