AI Engineering Consultant / Senior Consultant

Role

We are seeking an AI engineer capable of designing, building, and operationalising advanced AI, Machine Learning, and Generative AI systems at enterprise scale. The focus is to bridge the gap between AI prototypes and embedding data and AI solutions in business, ensuring they move from lab to live with the right solutions, practices, and guardrails for responsible scaling.

Responsibilities

• Assess and implement robust MLOps frameworks, governance, and best practices as per industry standards.
• Design and deliver end‑to‑end AI/ML systems, from data preparation and model development to deployment, feature store, model management, and monitoring.
• Deliver solutions using the latest Generative AI and Agentic Frameworks, such as ADK, Langgraph, Microsoft Agent Framework, Llamaindex, and others.
• Translate AI use‑case requirements into data and AI architectures using suitable cloud services across hyperscalers.
• Architect and implement Generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, GCP, or AWS.
• Embed safety, evaluation, and assurance mechanisms across the AI lifecycle, ensuring solutions are ethical, explainable, and responsible.
• Translate business and functional requirements into technical blueprints and guide multidisciplinary teams to execute them.
• Collaborate with Product Managers, Data Scientists, and Business stakeholders to ensure AI solutions drive business value and impact.

Profile

• Experience in a major consulting firm or industry with a consulting mindset and proven ability to succeed in a matrixed organisation, securing support and commitment from peers, client sponsors, and stakeholders.
• Experience designing and implementing MLOps strategy and framework, with a track record of delivering AI/ML solutions at scale from concept to production.
• Deep understanding of Generative AI and Agentic AI, including RAG pipelines, embeddings, evaluation harnesses, and orchestration frameworks.
• Experience designing cloud‑native data and AI architectures across Azure, GCP, AWS, and/or Databricks.
• Demonstrated ability to show how scaling AI unlocks business value and impact.

Technical Expertise

• Experience with at least one major cloud platform: Azure (Foundry, AI Studio, OpenAI, AKS), GCP (Vertex AI, Cloud Run), or AWS (Bedrock, SageMaker).
• Experience building and automating AI/ML pipelines using tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow, or Google ADK.
• Hands‑on experience with Generative and Agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, Google ADK, or similar.
• Ability to design and implement RAG pipelines, agentic workflows, MCP, and integration with LLM APIs (OpenAI, Anthropic, Hugging Face, or similar).
• Proficiency in CI/CD and containerisation: GitHub Actions, Azure DevOps, Docker, Kubernetes.

Nice to Have

• Familiarity with evaluating AI system performance, including prompt evaluation, A/B testing, and quality assessment frameworks.
• Understanding of modern data patterns: lakehouse architectures, vector databases, relational/NoSQL stores.
• Familiarity with API gateways, event streaming, and general integration patterns.

Eligibility

• Must have resided in the UK for the last 5 years to be eligible for this role.

EEO

We are an equal opportunity employer. All qualified applicants will receive equal consideration for employment and career opportunities. We are committed to diversity, inclusion, and fostering an environment where all employees can bring their whole selves to work.

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