Pre Sales AI Consultant

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The purpose of a Pre Sales AI Consultant is to shape and communicate credible AI-enabled solutions that address customer problems, support responsible AI adoption and help win deliverable work.  A Pre Sales AI Consultant helps customers understand where artificial intelligence, data and digital services can solve real business problems. The role combines AI credibility, consulting judgement, commercial awareness and strong communication skills to shape responsible, deliverable solutions that customers can trust and Kainos can confidently deliver.

Working across the sales lifecycle, the role partners with Sales, Bid, AI/Data, Architecture and Delivery specialists to understand customer needs, shape credible AI-led propositions, lead solution input into bids and support customer engagement through workshops, demonstrations, presentations and proofs of concept. This is a client-facing role for someone who can operate confidently with senior customer stakeholders, turning complex AI concepts into clear, commercially viable and compelling solutions, bringing in deeper AI, data, architecture or delivery expertise when needed.

Key responsibilities
1. Build trusted customer and stakeholder relationships Translate complex AI concepts into clear business value, public outcomes, delivery approaches and procurement-ready solution narratives. Act as a strategic advisor throughout opportunity development, from early market engagement and qualification through to bid response and transition into delivery. Communicate complex AI, data and delivery concepts in clear, accessible language for executive, commercial, technical and non-technical audiences.

Facilitate customer workshops, briefings, presentations, demonstrations and proofs of concept that bring AI opportunities and solution options to life.
2. Understand customer problems and shape viable AI solutions Lead discovery conversations, workshops and early solution shaping activity to understand customer goals, pain points, constraints, data readiness, risk appetite and success measures. Shape practical, commercially viable AI solutions that balance customer outcomes, technical feasibility, data foundations, adoption needs, responsible AI controls, delivery risk and value. Help customers understand the opportunities, benefits, risks, delivery considerations and governance requirements associated with AI adoption.

3. Lead AI solution input into bids and proposals Own the AI solution narrative for bids, proposals, frameworks, procurements and competitive opportunities, ensuring customer outcomes, win themes, AI differentiators, data considerations and responsible AI controls are clearly reflected. Bring together input from AI, data, architecture, security, governance and delivery specialists to strengthen solution quality, estimation, data readiness, risk management and customer confidence.

Develop high-quality written responses that explain the proposed AI solution, its value, how it will be delivered, how risks will be managed and why it is credible. Lead solution reviews, challenging assumptions and assuring the quality, credibility, responsible use and deliverability of proposed AI commitments.
4. Develop reusable assets and sales enablement material Create reusable assets that support customer engagement and future sales, such as AI use case patterns, discovery materials, demo scripts, proposal content, evaluation approaches and proof of concept approaches. Develop credible AI propositions and sales enablement material that respond to customer demand, reflect technology and market trends, and are grounded in deliverable capability.

5. Stay current with AI, data, market and industry trends Maintain a strong awareness of relevant AI, data, responsible AI, regulatory and public sector trends, and apply that knowledge in customer conversations, solution shaping, propositions and bid responses. Essential experience and skills Experience in technical pre-sales, AI or data consulting, digital transformation, business development or a closely related client-facing technology role.

Strong technical credibility in AI-enabled solutions, with the ability to understand, shape and explain how AI can be applied safely and effectively in complex organisational environments. Deep understanding of modern AI concepts and adoption patterns, including generative AI, large language…