Pre Sales AI Consultant

🏢 Kainos · all Kainos jobs
📍 United Kingdom
📅 Posted 2026-08-22 · via Himalayas
🏷 Pre-Sales-AI-Specialist,AI-Consulting,Pre-Sales-Engineer,Solutions-Architect,Sales-Engineering,Pre-Sales-Solutions-Consultant,Presale-Consultant,Pre-Sales-Consultant,AI-Solutions-Presales,Pre-Sales-Consulting,AI-Sales-Consulting,AI-Presales,AI-Consulting-Sales,IT-Presales-Consultant
Apply on original site ↗

Join Kainos and Shape the Future

At Kainos , we’re problem solvers, innovators, and collaborators - driven by a shared mission to create real impact. Whether we’re transforming digital services for millions, delivering cutting-edge Workday solutions, or pushing the boundaries of technology, we do it together.

We believe in a people-first culture , where your ideas are valued, your growth is supported, and your contributions truly make a difference. Here, you’ll be part of a diverse, ambitious team that celebrates creativity and collaboration.

Ready to make your mark? Join us and be part of something bigger.

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

← All remote jobs