AI / ML Solutions Architect

AI / ML Solutions Architect (Contract)

We’re looking for an experienced AI / ML Solutions Architect to join a major enterprise AI transformation programme. This role is ideal for someone who can combine deep technical expertise with strong consulting skills to design, architect and deliver scalable AI solutions across enterprise environments, including modern data platforms such as Snowflake .

Key Responsibilities

• Design and deliver enterprise-scale AI and Machine Learning solutions.
• Architect end-to-end AI platforms, integrating LLMs, machine learning and modern data ecosystems.
• Work closely with customers and stakeholders to identify AI use cases and translate business requirements into scalable technical solutions.
• Lead the implementation and production deployment of AI/ML solutions, ensuring security, scalability and governance.
• Provide technical leadership and architectural best practices throughout the project lifecycle.

Required Experience

• Significant commercial experience delivering LLM and Generative AI solutions.
• Strong hands-on experience with:
• Natural Language Processing (NLP)
• Document extraction, OCR and intelligent document processing
• Retrieval-Augmented Generation (RAG)
• Prompt engineering and LLM-based applications
• Significant production Machine Learning experience, including:
• Classification models (e.g. Gradient Boosting, Logistic Regression)
• Sequence modelling
• Experiment design, statistical evaluation and model validation
• Model interpretability techniques (e.g. SHAP)
• Experience deploying AI/ML solutions into production using MLOps best practices.
• Strong understanding of cloud-native architectures and enterprise data platforms.
• Experience designing scalable, secure AI solutions within enterprise environments.
• Excellent stakeholder management and communication skills.

Desirable Skills

• Experience working with Snowflake, including Snowflake Cortex, Snowpark, Snowflake ML or AI-powered analytics.
• Experience with Databricks, Azure ML, AWS SageMaker or similar ML platforms.
• Knowledge of LangChain, LangGraph, CrewAI or other AI orchestration frameworks.
• Experience building RAG solutions and working with vector databases.
• Background delivering AI solutions within regulated industries such as financial services, insurance or healthcare.

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