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Generative AI Engineer

Salary
£545/day
Hiring from
United Kingdom
Work type
Hybrid
Posted
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AI Consultant / Engineer – Generative AI & Agentic AI

Location: Cardiff / Manchester / London, UK

Work Model: Hybrid – 2 Days per Week in the Office

Contract Duration: 12 Months

Rate: £545 per day (inside IR35)


Are you an experienced AI Consultant / Engineer with strong hands-on expertise in Generative AI, Agentic AI, Python, Google Gemini, RAG and Google Cloud Platform (GCP)

We’re looking for a highly skilled AI Consultant / Engineer to design, develop and deploy enterprise-scale AI solutions within the banking and financial services sector. This role offers the opportunity to work on innovative AI initiatives, leveraging Google Gemini, open-source Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and agent-based AI architectures.

You will work closely with business stakeholders, architects and engineering teams to translate business requirements into scalable, secure and production-ready AI applications. The role will focus on AI engineering, cloud-native development, model integration, automation and MLOps, helping deliver intelligent solutions that improve customer experiences, operational efficiency and business innovation.


Key Responsibilities

  • Design, develop and deploy scalable Generative AI and Agentic AI solutions using Google Gemini and open-source LLMs.
  • Build and optimise RAG-based applications using enterprise knowledge sources and vector search technologies.
  • Develop AI-powered APIs, microservices and reusable components for enterprise applications.
  • Fine-tune, evaluate, integrate and operationalise foundation models to meet business requirements.
  • Implement AI agents and orchestration workflows using Agent Development Kits (ADK), Model Context Protocol (MCP) and related frameworks.
  • Deploy and manage AI workloads on Google Cloud Platform (GCP) using cloud-native technologies.
  • Implement MLOps practices covering model deployment, monitoring, CI/CD, automation and lifecycle management.
  • Apply AI security, governance, guardrails and responsible AI practices to enterprise solutions.
  • Monitor production systems, troubleshoot issues and optimise AI application performance, scalability and reliability.
  • Collaborate with business stakeholders, architects and engineering teams to deliver high-quality AI solutions and promote engineering best practices.


Required Skills & Experience

  • Strong hands-on experience in Generative AI, Agentic AI and Large Language Model (LLM) implementations.
  • Proven experience with Google Gemini and open-source LLM ecosystems.
  • Advanced Python development skills and experience building enterprise-grade applications.
  • Strong experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
  • Understanding of Agent Development Kits (ADK), Model Context Protocol (MCP) and AI orchestration frameworks.
  • Experience developing REST APIs, microservices and distributed applications.
  • Hands-on experience with Google Cloud Platform (GCP) and cloud-native architectures.
  • Strong understanding of MLOps, CI/CD pipelines, model lifecycle management and deployment automation.
  • Experience with Docker, Kubernetes and container orchestration.
  • Excellent problem-solving, communication and stakeholder management skills, with the ability to translate business requirements into technical solutions.


Desirable Experience

  • Experience within banking, financial services, insurance or other regulated industries.
  • Experience with frameworks such as LangChain, LangGraph, LlamaIndex, CrewAI or Semantic Kernel.
  • Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB or pgVector.
  • Knowledge of AI governance, Responsible AI, compliance and model risk management.
  • Experience with prompt engineering, AI guardrails, LLM security and evaluation techniques.
  • Experience implementing observability and monitoring for AI platforms and production workloads.
  • Understanding of event-driven architectures, messaging platforms and enterprise integration patterns.
  • Exposure to data engineering, enterprise data platforms and feature stores.
  • Experience leading technical design discussions and collaborating across multidisciplinary engineering teams.
  • Relevant Google Cloud, Generative AI, machine learning or Kubernetes certifications.


Apply now to learn more about this AI Consultant / Engineer opportunity, working on enterprise-scale Generative AI and Agentic AI solutions within financial services, using cutting-edge technologies including Google Gemini, Python, RAG, ADK/MCP and GCP.

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