Senior AI Developer

We are looking for a highly skilled Senior AI Developer with strong hands-on experience in machine learning, deep learning, generative AI, MLOps, cloud AI platforms, NLP, computer vision, and production-grade AI deployment. This is a senior technical role suited to someone who has already built and deployed AI solutions in real-world business environments. The successful candidate will help design, build, deploy, and operate AI models and pipelines, while also contributing to the technical standards and foundations of a newly established AI function.

The ideal candidate must be comfortable working in a greenfield environment, where they will be expected to work independently, solve complex technical problems, and help shape the client’s AI delivery capability.

• Design, build, train, test, and deploy machine learning and deep learning models.
• Develop end-to-end AI pipelines covering data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
• Build scalable AI solutions that can operate reliably in production environments.
• Optimise models for performance, accuracy, scalability, and reliability.
• Work with structured and unstructured data to develop practical AI solutions.
• Translate business and technical requirements into AI-driven solutions.

• Implement and fine-tune Large Language Models for enterprise use cases.
• Develop generative AI solutions using modern frameworks and tools.
• Design and build Retrieval-Augmented Generation architectures.
• Work with embeddings, vector databases, semantic search, and document intelligence.
• Evaluate LLM performance, accuracy, hallucination risk, and output quality.

• Establish and manage MLOps frameworks for production AI delivery.
• Implement model versioning, monitoring, retraining, performance tracking, and governance.
• Build automated AI/ML pipelines and deployment workflows.
• Implement CI/CD practices for machine learning and AI systems.
• Monitor production models for drift, degradation, and performance issues.
• Ensure AI solutions are secure, scalable, maintainable, and reliable.

• Deploy and manage AI workloads on cloud platforms.
• Work with platforms such as Azure AI / Azure ML, AWS Sage Maker, and Google Vertex AI.
• Support batch and real-time inference workloads.
• Integrate AI models with enterprise applications and data platforms.
• Ensure cloud-based AI deployments meet performance and reliability standards.

• Build NLP solutions including text processing, classification, named entity recognition, and transformer-based models.
• Develop computer vision solutions such as image classification, object detection, and segmentation.
• Deploy NLP and computer vision models into production environments where required.

• Work directly with business and technical stakeholders.
• Contribute to AI technical standards, best practices, and delivery frameworks.
• Produce clear technical documentation, model cards, and deployment guides.
• Support knowledge transfer within the team.
• Mentor junior team members as the AI function grows.
• Operate independently and take ownership of AI solution delivery.

• Model training and optimisation
• RAG architectures
• CI/CD for ML
• Orchestration tools
• Model lifecycle management
• Production deployment practices

• Tensor Flow
• Py Torch

• Azure AI / Azure Machine Learning
• AWS Sage Maker
• Google Vertex AI

• Text processing
• Named entity recognition
• Text classification
• Transformer-based models
• NLP model deployment