AI Pre-Sales Integration Architect 

I am working with a leading technology services organisation seeking a senior AI Pre-Sales Integration Architect to act as the technical authority between customers, sales teams, and delivery architects.
This is a customer-facing, pre-sales and solution architecture role, focused on shaping and positioning AI solutions rather than pure research or back-office delivery. You’ll lead AI engagements end to end — from early discovery and use-case definition through to high-level architecture and platform design.
The role covers areas such as Predictive AI, Machine Learning and Generative AI, MLOps, data pipelines and modern AI platforms, across both cloud and private infrastructure.
Alongside customer work, you’ll contribute to the development of AI offerings, standards and propositions, while supporting and mentoring other architects within the wider team.

Key Responsibilities
•    Act as the AI subject matter expert in customer engagements, working directly with business stakeholders, data teams and IT operations.
•    Lead discovery and design of AI strategies, governance models and platform architectures aligned to business outcomes.
•    Design end-to-end AI solutions, including data ingestion, feature engineering, ML/GenAI models, MLOps and deployment.
•    Support pre-sales activity, including solution shaping, technical validation, demos and customer presentations.
•    Bridge multiple technology domains (cloud, hybrid infrastructure, data platforms, security, DevOps) into cohesive AI solutions.
•    Contribute to the evolution of AI propositions, offerings and best practices.
•    Mentor and support less experienced team members, contributing to team-wide capability development.

Skills & Experience Required
•    5+ years’ experience in AI / ML, data platforms, MLOps or advanced analytics roles.
•    Recognised as a technical expert by colleagues, partners and customers.
•    Strong hands-on knowledge of AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn.
•    Experience working with cloud AI platforms (AWS, Azure or GCP).
•    Exposure to private / on-prem AI platforms (e.g. NVIDIA-based stacks, private AI platforms).
•    Solid understanding of data engineering concepts (ETL, data lakes, Spark or similar).
•    Experience designing scalable, distributed systems.
•    Familiarity with model lifecycle management and MLOps practices.
•    Proven ability to align AI initiatives to business outcomes and shape practical use cases.
•    Experience in client-facing and pre-sales environments.
•    Broad technology background, with depth in at least one of: Cloud, Hybrid Infrastructure, Workspace or Security.
•    Strong commercial awareness; channel or partner experience is advantageous.
•    Experience mentoring or leading small teams is a plus.

Personal Attributes
•    Credible, ambitious and accountable, with the confidence to influence senior stakeholders.
•    Clear, concise communicator — comfortable presenting complex concepts to both technical and non-technical audiences.
•    Detail-oriented, organised, and able to manage multiple priorities in a fast-moving environment.
•    Naturally curious, with a strong appetite for learning and staying current with AI trends.
•    Proactive, pragmatic, and delivery-focused with a strong “can-do” mindset.
•    Willing to travel occasionally while maintaining a healthy work–life balance.