Application Architect

Application Architect L1 (AI/ML & Agentic AI Platforms)

Skill Group: GCP AI/ML – Vertex AI

Location: Manchester, UK (2 Days Onsite)

Employment Type: Long-Term Contract

Role Overview

We are seeking an experienced Application Architect L1 with strong expertise in Google Cloud AI/ML technologies, Agentic AI systems, and modern cloud-native architecture. The ideal candidate will design and deliver scalable AI-powered enterprise solutions using Google Gemini on Vertex AI, orchestration frameworks, and knowledge-driven architectures.

This role requires deep technical proficiency in Python, Google Cloud Platform (GCP), containerized deployments, and semantic data modeling, along with experience building intelligent systems powered by LLMs, RAG pipelines, and autonomous agents.

The position is based in Manchester, UK, with a hybrid working model requiring 2 days onsite per week.

Key Responsibilities

• Design and architect enterprise-grade AI/ML solutions on Google Cloud Platform (GCP).
• Develop AI applications using Google Gemini models via Vertex AI.
• Build intelligent agent workflows using Google Agent Development Kit (ADK).
• Architect and deploy scalable microservices using Python and FastAPI.
• Implement cloud-native deployments using Docker and Google Kubernetes Engine (GKE).
• Design and manage Knowledge Graphs, RDF/property graph structures, and semantic models.
• Build Retrieval-Augmented Generation (RAG) pipelines integrating enterprise knowledge sources and vector search.
• Collaborate with engineering, product, and business teams to define scalable AI architectures.
• Optimize application performance, scalability, security, and reliability.
• Evaluate and improve LLM outputs using frameworks such as ARES, Ragas, and DeepEval.
• Provide architectural guidance, technical leadership, and best practices to development teams.

Required Skills

• Strong hands-on experience with:
• Google Gemini (Vertex AI)
• Google Agent Development Kit (ADK)
• Python
• Google Cloud Platform (GCP)
• Google Kubernetes Engine (GKE)
• Docker
• Knowledge Graphs
• RDF / Property Graphs
• Semantic Modelling
• Experience designing scalable cloud-native and distributed systems.
• Strong understanding of AI/ML solution architecture and LLM integration patterns.
• Experience with API-driven and microservices-based architectures.
• Excellent communication and stakeholder management skills.