AI Engineer

Project Global Limited; Greater London; Hybrid; GBP 77,000 - 144,000; Full time

Benefits offered by this job

Remote-friendly UK

Job summary

Project Global Limited is seeking an AI Engineer/Consultant to join a hybrid-based team working primarily in the UK (Cardiff / Manchester / London offices with 2 days onsite). The contract is 12 months with a day-rate reflecting market norms, and the role focuses on building enterprise-grade Generative AI and AI governance solutions.

You’ll leverage Gemini, Open-Source LLMs, RAG, ADK/MCP, and GCP to deliver scalable AI platforms, APIs, and microservices while ensuring performance, security, and

Qualifications

• Experience in Generative AI and LLM implementations.
• Proven expertise with Gemini and Open-Source LLM ecosystems.
• Advanced Python development for enterprise apps.
• Experience designing and implementing RAG architectures.
• Knowledge of ADK/MCP and AI orchestration frameworks.
• Experience building REST APIs, microservices, distributed apps.
• Hands-on with GCP services and cloud-native architectures.
• Strong MLOps, CI/CD, model lifecycle management, and automation.

Responsibilities

• Design, develop, and implement scalable Generative AI and Agentic AI solutions.
• Build and optimise RAG-based applications leveraging enterprise knowledge sources.
• Develop AI-powered APIs, microservices, and reusable components.
• Fine-tune and operationalise foundation models to meet business needs.
• Collaborate with stakeholders to translate use cases into technical solutions.
• Deploy and manage AI workloads on GCP with modern cloud-native tech.
• Apply MLOps best practices including CI/CD, monitoring, and governance.
• Ensure enterprise security, reliability, and performance of AI solutions.
• Perform performance tuning, observability, and root cause analysis.
• Provide technical leadership and mentoring for AI engineering teams.

Skills

Generative AI

Agentic AI

LLM implementations

Google Gemini

Python development

REST APIs

Microservices

GCP

MLOps

Docker & Kubernetes

AI governance & security

Tools

LangChain

LangGraph

LlamaIndex

CrewAI

Semantic Kernel

Pinecone

Weaviate

ChromaDB

pgVector

Job description

AI Engineer

Our client, a leading global supplier for IT services, requires AI Consultant/Engineer to be based at their client's office in Cardiff / Manchester / London, UK.

This is a hybrid role - you can work remotely in the UK and attend the Cardiff / Manchester / London office 2 days per week .

This is a 12 month temporary contract to start asap

Day rate: Competitive Market rate

Join a high-performing engineering team delivering next-generation AI and digital transformation solutions within the financial services sector. This role offers the opportunity to design, build, and deploy enterprise-scale Generative AI and Agentic AI solutions that enhance customer experiences, improve operational efficiency, and accelerate business innovation.

You will work with cutting-edge technologies including Google Gemini, Open-Source Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agent Development Kits (ADK), Model Context Protocol (MCP), and Google Cloud Platform (GCP). The role provides exposure to cloud-native architecture, MLOps, AI governance, and enterprise-scale solution delivery, enabling you to contribute to transformational programmes while remaining at the forefront of AI innovation.

Key Responsibilities

• Design, develop, and implement scalable Generative AI and Agentic AI solutions using Gemini and Open-Source LLMs.
• Build and optimise RAG-based applications leveraging enterprise knowledge sources and vector search technologies.
• Develop AI-powered APIs, microservices, and reusable components to support business-critical applications.
• Fine-tune, evaluate, onboard, and operationalise foundation models to meet specific business requirements.
• Collaborate with business stakeholders, architects, and engineering teams to translate use cases into technical solutions.
• Deploy and manage AI workloads on GCP using modern cloud-native and container technologies.
• Implement MLOps best practices covering model deployment, monitoring, CI/CD, automation, and governance.
• Ensure solutions meet enterprise standards for security, reliability, scalability, and performance.
• Conduct performance tuning, observability monitoring, and root cause analysis for production systems.
• Provide technical leadership, mentoring, and support for AI engineering best practices across delivery teams.

Key Requirements

Essential Skills:

• Strong hands-on experience in Generative AI, Agentic AI, and Large Language Model (LLM) implementations.
• Proven expertise with Google Gemini and Open-Source LLM ecosystems.
• Advanced Python development skills with experience building enterprise-grade applications.
• Experience designing and implementing Retrieval-Augmented Generation (RAG) architectures.
• Strong understanding of ADK, MCP, AI orchestration frameworks, and integration patterns.
• Experience developing REST APIs, microservices, and distributed applications.
• Hands-on experience with Google Cloud Platform (GCP) services and cloud-native architectures.
• Strong knowledge of MLOps practices, CI/CD pipelines, model lifecycle management, and automation.
• Experience with Docker, Kubernetes, container orchestration, and scalable deployment strategies.
• Excellent analytical, problem-solving, stakeholder management, and communication skills.

Desirable Skills:

• Experience within financial services, banking, insurance, or other regulated industries.
• Expertise in GenAI, Gemini, and Open-Source LLMs, including fine-tuning and onboarding.
• Strong experience in Python, RAG, ADK/MCP, APIs, and microservices.Skilled in GCP, MLOps, CI/CD, Docker, Kubernetes, and scalable AI solutions.
• Proficient in observability, performance optimization, security, and production reliability.
• Knowledge of Responsible AI, AI governance, compliance, and model risk management.
• Experience with LangChain, LangGraph, LlamaIndex, CrewAI, Semantic Kernel, or similar frameworks.
• Familiarity with vector databases such as Pinecone, Weaviate, ChromaDB, or pgVector.
• Experience implementing observability and monitoring solutions for AI platforms.
• Understanding of event-driven architectures, messaging platforms, and enterprise integration patterns.
• Exposure to data engineering, feature stores, and enterprise data platforms.
• Experience leading technical design discussions and architecture reviews.
• Knowledge of AI security, prompt engineering, guardrails, and reliability engineering practices.
• Relevant cloud and AI certifications (Google Cloud, Kubernetes, Generative AI, or ML certifications).

Due to the volume of applications received, unfortunately we cannot respond to everyone.

If you do not hear back from us within 7 days of sending your application, please assume that you have not been successful on this occasion.

Please do keep an eye on our website https://projectrecruit.com/jobs/ for future roles.