Senior AI Engineer
Sheffield - 1-2x week in office
Salary: £80,000 - £90,000
This is an exciting opportunity to join a business that is investing heavily in AI and modern cloud technologies. You will play a key role in building AI‑driven products that have a direct impact on customer experience, operational efficiency and the future of their platform.
The Company
They are a tech‑forward insurance organisation with a strong focus on delivering smarter, more personalised digital products. Their teams combine data, engineering and customer expertise to create solutions that simplify complex challenges for their users. Innovation, collaboration and a flexible working culture are at the heart of how they operate. They continue to scale their AI capability and are looking for someone who can help shape this next phase of growth.
The Role
In this AI Platform Engineer role, you will:
• Design, build and operate AI‑first products that deliver measurable value.
• Develop and deploy production‑grade AI agents on GCP using ADK, integrating with internal systems via REST and JSON APIs.
• Build and maintain robust evaluation and monitoring frameworks, including online and offline testing, A/B experiments and performance dashboards.
• Integrate AI agent functionality with applications through MCP servers and reliable tool configurations.
• Develop secure and scalable RAG pipelines, including ingestion, text processing, metadata handling and vector search in GCP.
• Embed security, compliance, GDPR controls and best‑practice engineering with clear documentation and stakeholder collaboration.
Your Skills and Experience
To be successful, you will bring:
• Strong Python skills for backend services, SDKs, API development, authentication and testing.
• Hands‑on experience working with LLMs, embeddings, prompt engineering, tool calling and RAG design.
• Practical knowledge of GCP services including Vertex AI, Model Garden, BigQuery, Cloud Run and Google’s ADK.
• Experience with document and data processing using tools such as Apache Tika, plus storage or caching technologies like Postgres, Redis, GCS or BigQuery.
• Solid DevOps practices including CI/CD, Docker, observability and automated testing.
• A product‑led mindset with a strong understanding of security, IAM, auditability and defining success metrics.
What They Offer
• Opportunities to shape AI products from the ground up.
• A collaborative environment that encourages innovation and career progression.
How to Apply
If you are excited about building production‑ready AI systems and want to drive meaningful impact, please apply with your CV.