Solution Engineer (AI)

Location: London, United Kingdom

Company

Snowflake provides cloud data platforms and AI capabilities for enterprise customers.

What you will do

• Support end-to-end technical sales engagements for one strategic global financial services account, from discovery and qualification through proof-of-concept delivery and technical close.
• Build and deliver tailored demonstrations and solution presentations that connect Snowflake capabilities to customer data challenges and business objectives.
• Assist with proof-of-concept engagements covering risk analytics, regulatory data platforms, fraud detection, customer intelligence, and AI/ML workloads.
• Develop working knowledge of the customer's data architecture, cloud environment, and technology stack.
• Support the Account Executive with deal activity, technical RFP responses, and removal of technical blockers.
• Coordinate with Professional Services, Support, Product, data engineers, architects, and technical managers to provide appropriate customer resources.

Requirements

• 5+ years of experience in pre-sales solution engineering, data engineering, or technical consulting in enterprise B2B technology, with exposure to financial services organisations.
• Foundational understanding of cloud data platforms and modern data architectures, with the ability to develop deeper expertise quickly.
• Proficiency in SQL and Python, including writing and debugging scripts, building proof-of-concept pipelines, and working in technical customer environments.
• Clear communication skills for translating technical concepts to engineering and business audiences within a financial institution.
• Strong organisational skills and the ability to manage multiple workstreams during an active sales cycle.
• Curiosity about AI and data technology, with eagerness to develop expertise in Snowflake Cortex AI capabilities and apply them in financial services contexts.
• Growth mindset, receptiveness to feedback, interest in coaching, and motivation to progress toward senior solution engineering responsibilities.

Nice to have

• Hands-on exposure to Snowflake through work projects, certifications, or personal use.
• Internships or placements in pre-sales, technical consulting, or data engineering within technology companies.
• Familiarity with dbt, Kafka, Spark, or equivalent data tools used in financial services environments.
• Coursework or foundational knowledge of risk management, regulatory reporting, or fraud analytics.
• Experience with customer-facing presentations, demonstrations, or hackathons.

Culture & Benefits

• AI-native, experimental approach to solving problems and improving how work gets done.
• Low-ego environment focused on curiosity, feedback, coaching, and challenging ordinary thinking.
• Opportunity to work with a strategically important, data-rich financial services account.
• Collaboration with Professional Services, Support, Product, Account Executive, and customer technical teams.