AI Engineer

Great ideas come from different minds. That's why we bring together engineers, data scientists, analysts, researchers, and innovators from diverse backgrounds — giving them the trust, tools, and freedom to solve complex problems and deliver meaningful impact.

As technology continues to evolve, so do we. We work on cutting‑edge solutions that transform organisations through Artificial Intelligence, Machine Learning, Data Science, Cloud Technologies, and Advanced Analytics.

We are seeking talented AI Engineers to join our growing capability and help design, develop, and deploy AI‑powered solutions that deliver real‑world outcomes across government, defence, national security, and commercial sector.

Role:
We are looking for experienced AI Engineers to strengthen our delivery capability across a range of AI and Machine Learning programs.

The successful candidates will work across the full AI lifecycle, from requirements gathering and solution design through to model development, deployment, optimisation, and operational support. This is a hands‑on technical role requiring strong software engineering practices combined with expertise in modern AI technologies, machine learning frameworks, and cloud‑native architecture.

You will collaborate with multidisciplinary teams to build scalable, secure, and production‑ready AI systems that solve complex business and operational challenges.

• Design, develop, and deploy AI and Machine Learning solutions to address complex customer requirements.
• Build scalable AI applications, services, and platforms using modern software engineering practices.
• Develop, evaluate, and optimise machine learning models, including Generative AI and Large Language Model (LLM) solutions.
• Integrate AI capabilities into enterprise systems, products, and operational environments.
• Support technical architecture, solution design, and technology selection activities.
• Ensure AI solutions are secure, reliable, maintainable, and aligned with customer needs.

• Design and develop AI‑enabled applications using Python and modern development frameworks.
• Build and deploy machine learning, deep‑learning, and Generative AI solutions.
• Develop and optimise Retrieval‑Augmented Generation (RAG) pipelines and LLM‑powered applications.
• Integrate AI services with cloud platforms, APIs, databases, and enterprise systems.
• Create scalable data processing and feature engineering pipelines.
• Implement MLOps practices including model deployment, monitoring, testing, and lifecycle management.
• Evaluate model performance and continuously improve accuracy, reliability, and efficiency.
• Apply software engineering best practices including version control, CI/CD, testing, and code reviews.
• Support technical investigations, proof‑of‑concepts, and innovation activities.
• Contribute to solution architecture and technical design decisions.
• Conduct trade‑off analysis across performance, scalability, cost, security, and maintainability.
• Support selection and evaluation of AI models, frameworks, and platforms.
• Ensure solutions align with enterprise architecture and governance requirements.

• Work closely with project managers, technical leads, and customer stakeholders to deliver successful outcomes.
• Translate business requirements into technical AI solutions.
• Provide technical guidance and expertise throughout the project lifecycle.
• Present findings, demonstrations, and recommendations to technical and non‑technical audiences.
• Identify risks, dependencies, and opportunities early to support successful delivery.
• Strong software engineering experience using Python.
• Experience with machine learning frameworks such as PyTorch, Tensor Flow, Scikit‑Learn, or equivalent.
• Experience developing Generative AI and LLM‑based applications.
• Knowledge of Retrieval‑Augmented Generation (RAG), vector databases, and prompt engineering techniques.
• Experience deploying applications within cloud environments such as AWS, Azure, or Google Cloud Platform.
• Understanding of APIs, microservices, and distributed systems architectures.
• Experience with containerisation technologies such as Docker and Kubernetes.
• Strong…