Senior Data & AI Solutions Architect - Pre-Sales

Technical Pre-Sales / Customer Solutions

Location: London, UK
- Hybrid Contract: Permanent
- Full-time (~1-2 days per week in office)
Package: £80, + 30% Bonus + 10% Shares + Benefits (see more below)

Appvia is a specialist platform engineering and AI enablement consultancy, helping organisations design, build, and operate modern cloud platforms and transform how software is delivered.

Our work spans platform engineering, software modernisation, data platforms, AI enablement, and managed services. We partner with public and private sector organisations to solve complex challenges, improve developer productivity, and unlock value from modern cloud and AI technologies.

As demand for our Data & AI capability continues to grow, we are investing heavily in building repeatable services, assets, and accelerators that help customers move from experimentation to real business outcomes.

We are looking for a senior, customer-facing Data & AI Solutions Architect to help shape and grow Appvia's Data & AI capability.

This is a high-impact role sitting at the intersection of Revenue, Engineering, and Product. Working closely with the Head of Cloud Solutions and the growing Data & AI Practice, you will help customers turn data into decisions and AI into value, while influencing Appvia's services, propositions, and go-to-market strategy.

With demand strongest around modern data platforms, we are looking for someone with deep expertise in data architecture and hands-on experience across modern data and AI technologies. You will own technical engagements from initial discovery through proof-of-value and into delivery handover, building trusted relationships with customers and guiding them from ideas to measurable outcomes.

This is a fantastic opportunity for a technically strong communicator who enjoys combining architecture, storytelling, and customer engagement, and who wants to play a key role in defining the future of Data & AI erview Process - 3 Stage

• Discovery conversation with Talent Acquisition
• Technical interview with Data & AI Practice
• Final interview with Leadership

• Partner with the Revenue team to shape account plans, opportunity strategy, and business objectives
• Technically qualify opportunities, validating customer fit, decision criteria, and clear paths to value
• Own the technical outcome of customer engagements from discovery through proof-of-value and into delivery
• Lead workshops to uncover business goals, technical constraints, and success criteria
• Qualify value, ROI, and TCO to help customers secure investment and stakeholder buy-in
• Support proposals, Statements of Work, RFI/RFP responses, and security questionnaires
• Design and deliver compelling demonstrations, proofs-of-concept, and technical deep dives
• Build reusable demo environments, reference architectures, and technical assets to accelerate future sales cycles
• Create segmented technical content, webinars, and industry-facing material with Marketing
• Develop relationships with cloud and SI partners to expand Appvia's reach and co-sell opportunities
• Represent Appvia at customer workshops, industry events, and community meetups
• Feed customer insight, competitive intelligence, and market trends back into Product and Professional Services

You are a technically strong communicator who enjoys engaging with customers and making complex ideas easy to understand. Equally comfortable presenting to C-level stakeholders or discussing architecture with engineers, you're passionate about helping organisations realise value from modern data and AI technologies.

You will bring:

• Experience in pre-sales, solution architecture, consulting, or technical evangelism within Data & AI
• Strong understanding of modern data platforms and data architecture
• Experience designing and explaining Lakehouse and Data Warehouse architectures using technologies such as Databricks, Snowflake, Microsoft Fabric, Big Query, Redshift, or similar
• Strong understanding of ETL/ELT, analytics and BI, stream vs batch processing, and Medallion Architecture
• Familiarity with the Data Science and ML lifecycle, including feature engineering, model training, monitoring, and MLOps
• Working knowledge of GenAI technologies, including RAG, MCP, vector databases, LLM providers, agentic workflows, and LLMOps
• Experience with cloud-native technologies across AWS, Azure, or GCP, including their Data and AI services
• Understanding of data governance, responsible AI, access…