Pre Sales AI Consultant

The purpose of a Pre Sales AI Consultant is to shape and communicate credible AI-enabled solutions that address customer problems, support responsible AIadoptionand help win deliverable work.

A Pre Sales AI Consultant helps customers understand where artificial intelligence, data and digital services can solvereal businessproblems. The role combines AI credibility, consulting judgement, commercialawarenessandstrong communicationskills 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,presentationsand proofs of concept.

This is a client-facing role for someone who canoperateconfidently with senior customer stakeholders, turningcomplex AI concepts into clear, commerciallyviableand compelling solutions, bringingin deeper AI, data,architectureor deliveryexpertisewhen needed.

Key responsibilities

1. Build trusted customer and stakeholder relationships

• Translate complexAIconcepts into clear businessvalue, publicoutcomes, deliveryapproachesand 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,dataand delivery concepts in clear, accessible language for executive, commercial,technicaland non-technical audiences.

• Facilitate customer workshops, briefings, presentations,demonstrationsand proofs of concept that bring AI opportunities and solution options to life.

2. Understand customer problems and shapeviableAI solutions

• Lead discovery conversations, workshops and early solution shaping activity to understand customer goals, pain points, constraints, data readiness, riskappetiteand success measures.

• Shape practical, commerciallyviableAI solutions that balance customer outcomes, technical feasibility, data foundations, adoption needs, responsible AI controls, deliveryriskand value.

• Help customers understand the opportunities, benefits, risks, deliveryconsiderationsand governance requirements associated with AI adoption.

3. Lead AI solution input into bids and proposals

• Own the AI solution narrative for bids, proposals, frameworks,procurementsand competitive opportunities, ensuring customer outcomes, win themes, AI differentiators, dataconsiderationsand responsible AI controls are clearly reflected.

• Bring together input from AI, data, architecture, security,governanceand delivery specialists to strengthen solution quality, estimation, data readiness, riskmanagementand 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, responsibleuseand 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, evaluationapproachesand 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,marketand 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,propositionsand bid responses.

Essential experience and skills

• Experience in technical pre-sales, AI or data consulting, digital transformation, businessdevelopmentor 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 model-enabled solutions, agentic workflows, data foundations, evaluation approaches, responsible AIcontrolsand production adoption.

• Experience shaping AI strategies, use case prioritisation, data readiness assessments, implementation roadmaps, customer demonstrations, proofs of concept or AI-focused proposition development.

• Proven ability to understand customer problems and shape practical, commerciallyviableAI solutions.

• Experience contributing to or owning AI solution input for bids, proposals, tenders,frameworksor complex sales opportunities.

• Strong communication,facilitationand stakeholder engagement skills, including the ability to produce clear bid responses and customer-facing AI material, and to work credibly with senior customer stakeholders and technical specialists.

• Ability to collaborate effectively with AI, data, architecture, delivery,salesand bid colleagues, drawing on expert input whilemaintaininga coherent solution narrative.

• Commercial awareness, including an understanding of value, risk, effort, delivery feasibility, data readiness and how proposed AI solutions support customer outcomes and business growth.

• Ability to manage multiple opportunities,deadlinesand stakeholder inputs in a high-pressure sales environment.

Desirable experience

• Experience working with public sector organisations, regulatedenvironmentsor complex procurement processes.