Senior AI Engineer Job at NTT DATA (Johannesburg)

Senior AI Engineer

NTT DATA

Location:
South Africa , Johannesburg

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

The Senior AI Engineer at NTT DATA will be responsible for designing and deploying innovative AI solutions, focusing on Generative AI and machine learning. The role requires a postgraduate qualification in a relevant field and 5-10 years of experience in AI or machine learning. Strong proficiency in Python and experience with ML frameworks are essential. NTT DATA is seeking an experienced Senior AI/Machine Learning Engineer with a strong Generative AI focus to join our AI practice in Johannesburg. This role will play a key part in designing, building, and deploying applied AI and GenAI solutions for enterprise clients across the Middle East & Africa region. 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.

Job Responsibility:

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
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
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
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

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
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)
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)
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

Additional Information:

Job Posted:
March 19, 2026

Employment Type:

Fulltime

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