Solutions Engineer (AI Platforms)

Solutions Engineer (AI Platforms) At-a-Glance - Mid-level engineering role deploying an AI platform into complex customer environments - Integration, configuration and extension of a proprietary AI operating system - Python, APIs, cloud infrastructure, LLM and agent tooling - Strong mentoring from senior engineers and a clear route to senior - Share options and a genuinely AI-first engineering culture About the Company My client is a UK technology company building an AI operating and orchestration layer that puts intelligent systems to work inside large, complex organisations where accuracy and accountability really matter. The platform is already live and in daily operational use with major customers. The engineering group is small, senior and unusually fast moving, with AI tooling built into how the team genuinely works rather than bolted on afterwards. The Role Getting a powerful AI platform to work inside a customer environment is a real engineering discipline, and this is a chance to learn it properly alongside people who already do it well. You will build integrations with customer data and systems, configure and extend the platform, and help make sure what goes live is robust and observable. You will have your own areas of ownership from early on, with senior engineers close by rather than looking over your shoulder. It suits someone a few solid years into their career who wants to get very good at AI engineering quickly. Key Responsibilities - Build integrations with customer data sources and systems - Configure and extend platform capability to meet customer requirements - Implement retrieval and agent configurations under senior guidance - Contribute to monitoring, observability and evaluation of live solutions - Diagnose and resolve issues in production and secure environments - Document deployment steps and patterns so they can be repeated - Take part actively in code and design review - Feed platform gaps and practical lessons back to core engineering What You'll Need Essential: - 2 to 4 years commercial software engineering experience - Solid Python and experience working with APIs and integrations - Some hands-on exposure to cloud infrastructure, ideally AWS - Practical interest in large language models and agent-based systems, whether professional or self-directed - Comfortable asking questions and working things out in unfamiliar territory - Eligible for UK security clearance Desirable / Nice to Have: - Any experience deploying software into customer or restricted environments - Familiarity with graph databases or vector retrieval infrastructure Why Apply? - Get properly good at AI engineering somewhere it is used in earnest - Platform already live with significant enterprise customers - Share options as part of the package - Modern AI tooling is standard practice, not a pilot scheme - Flexible working pattern - Real mentoring from a small, very senior engineering team - Clear and visible progression route to senior Next Steps Interested? Get in touch with Brendan McCrory at I can talk you through the team, the process and what the client is actually looking for before you decide. Benefits: Work From Home

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