Ai Solutions Architect At Plentific Ltd
Pubblicato il 03-09-2026 - Jack & Jill in Italia
Job Title AI Solutions Architect Salary Not Disclosed Company Description Plentific Ltd is a leading property management Saa S platform used by housing providers, councils, and property companies across the UK and Europe to manage repairs, tenancies, and resident communications at scale. Backed and growing, they are integrating sophisticated AI to modernize legacy property management workflows.
Job Description
As an AI Solutions Architect at Plentific Ltd, you will lead the design and deployment of production-ready LLM agents and RAG pipelines. Working within a Python-based stack, you will bridge the gap between product strategy and engineering execution, automating complex property management workflows to drive efficiency for housing officers across Europe.
Location
Remote, Italy Why this role is remarkable Lead the transition from legacy manual processes to AI-driven automation in a high-impact sector that manages essential housing services for communities. Own the technical direction for AI engineering, moving beyond experiments to ship production LLM features with real-world traffic and measurable impact.
Join a growing Saa S leader where you will have the autonomy to establish AI best practices within a sophisticated Python ecosystem and modern stack.
What You Will Do
Design and deliver production AI features, focusing on LLM-powered agents and RAG pipelines embedded in the core Python platform. Collaborate with product managers to identify high-value AI opportunities and implement end-to-end solutions, including evaluation frameworks and safety guardrails. Architect and maintain scalable MLOps infrastructure using tools like Fast API, Pydantic AI, Lang Graph, and Bento ML to support real-time traffic.
The ideal candidate 5+ years of experience in Python development, with proven expertise in building and deploying Fast API or Django applications in production environments. Demonstrated history of deploying LLM-based systems to production traffic, including hands-on experience with orchestration frameworks like Lang Graph or Pydantic AI. Strong background in building RAG pipelines and managing cloud-based MLOps tooling within AWS, GCP, or Azure environments to support scalable AI.