AI Engineer (Contract) - Part-Time

Job Description – AI / ML (GenAI & Banking)

12 months contract - Renewable

We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy enterprise-grade AI, Machine Learning (ML), and Generative AI (GenAI) solutions within a regulated banking environment. The successful candidate will play a key role in driving AI innovation from use-case discovery through production deployment while ensuring compliance with governance, risk, and regulatory standards.

Key Responsibilities

• Design, build, and deploy scalable AI, ML, and Generative AI solutions across the full development lifecycle.
• Develop intelligent applications including AI assistants, conversational chatbots, autonomous agents, recommendation engines, and predictive analytics models.
• Partner with business stakeholders to identify, assess, and prioritize high-value AI use cases.
• Lead proof-of-concepts (POCs), experimentation, model testing, and production implementations.
• Implement model evaluation frameworks, benchmark testing, and performance monitoring processes.

• Develop and optimize machine learning models from data preparation through deployment.
• Perform feature engineering, model training, validation, tuning, and optimization.
• Establish MLOps pipelines to automate model deployment, monitoring, and retraining.
• Monitor model performance, drift, bias, and data quality to ensure sustainable outcomes.

• Implement AI governance frameworks, controls, and audit requirements.
• Maintain model documentation, validation reports, and governance artefacts.

Required Skills & Experience

• 5+ years of experience in AI, Machine Learning, Data Science, or Advanced Analytics.
• Strong expertise in Generative AI, Large Language Models (LLMs), Agentic AI, RAG architectures, Prompt Engineering, and AI Orchestration Frameworks.
• Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, and related AI ecosystems.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Strong knowledge of MLOps, DataOps, model governance, AI risk management, and operationalization of AI solutions.
• Experience within banking, financial services, or other highly regulated industries is highly preferred.
• Excellent stakeholder management, communication, and problem-solving skills.

Core Competencies

• Machine Learning & Advanced Analytics
• Generative AI & Large Language Models (LLMs)
• Agentic AI & Intelligent Automation
• Retrieval-Augmented Generation (RAG)
• Feature Engineering & Model Optimization
• MLOps & DataOps
• AI Governance & Responsible AI