Artificial Intelligence Consultant

Senior Consultant AI Engineering Consultant

We are seeking a Senior AI Consultant who can design, build, and ope rationalise advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The role focuses on bridging the gap between AI prototypes and fully embedded business solutions. You will be responsible for scaling AI solutions responsibly and reliably, ensuring measurable business impact while implementing ethical and robust AI practices.

• Lead the design and delivery of end-to-end AI/ML systems, from data preparation and feature engineering to model development, deployment, and monitoring.
• Implement robust MLOps frameworks, governance structures, and best practices across projects.
• Deploy Generative AI and Agentic AI solutions, including retrieval-augmented generation (RAG) pipelines, agentic workflows, and orchestration of large language models.
• Translate AI use case requirements into scalable and efficient data and AI architectures.
• Design cloud-native AI solutions across multiple cloud providers and environments.
• Build feature stores, model management systems, and pipelines for production-grade deployment.
• embed safety, evaluation, and assurance mechanisms across the AI lifecycle.
• Ensure AI systems are ethical, explainable, and responsible, with built-in evaluation frameworks.
• Work closely with product managers, data scientists, and business stakeholders to ensure AI solutions deliver tangible business value.
• Translate business and functional requirements into technical blueprints and guide multi-disciplinary teams to execute them.
• Support proposals, client demos, and proofs-of-concept showcasing AI delivery patterns.
• Develop reusable assets and internal frameworks to accelerate AI delivery across teams.
• Contribute to thought leadership, research, and internal innovation initiatives in areas such as LLMOps, agentic AI, and evaluation frameworks.

• Proven ability to work in a consulting environment or industry with a consulting mindset. Experienced in influencing both technical and non-technical stakeholders.
• Extensive experience designing and implementing AI/ML solutions at scale, including MLOps frameworks and pipelines.
• Strong understanding of RAG pipelines, embeddings, agentic orchestration, and evaluation frameworks.
• Expertise in designing cloud-native data and AI architectures across major cloud platforms.
• Demonstrated ability to deliver measurable business outcomes from
• Experience with at least one major cloud provider for AI/ML solutions.
• Hands‑on experience with automation frameworks, feature stores, and model management systems.
• Familiarity with building LLM-based workflows and knowledge integration pipelines.
• Ability to design retrieval-augmented generation pipelines, agentic workflows, and integrate with LLM APIs.
• Experience with Git Ops, Docker, Kubernetes, or equivalent tools.