Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Artificial Intelligence Engineer

Eames Consulting
City of London
2 days ago
Create job alert

Junior AI/ML Azure Engineer / 6 months / Hybrid London / Start ASAP


My client is setting up a brand new AI/ML function and within this capability, we are looking for a Azure AI MLOps Engineer professional. The role is based within the IT department on the AI function, located in my clients London headquarters building.

We are seeking a highly skilled and experienced Azure AI Engineer to design, develop and implement the AI and ML applications on the Azure platform. You will have adequate knowledge in deploying, integrating, testing and securing Azure AI Services encompassing AI and ML functions. You will be critical in creating intelligent AI applications. You will work closely with cross-functional teams to conceptualise, design, test, and deploy AI projects that drive innovation and provide value in the rapidly evolving field of artificial intelligence.

The AI IT application development uses Agile software delivery on Azure cloud technologies. The development uses a platform built using Python technologies together with commercially available off the shelf software products with the clients solution architecture team guidance.


Job Responsibilities


  • Build, develop and deploy AI powered applications using Python and related frameworks
  • Utilise Python and other relevant programming languages to build intelligent applications on the Azure platform.
  • Design and develop Azure AI Services proficiently; Develop solutions using Azure AI Prompt Flow;
  • Setup and develop data ingestion pipelines and components; design and develop efficient ingestion methodologies
  • Developing search related components using Azure AI Search (Vector Store)
  • Developing and deploying AI/ML models on Azure technologies for business teams
  • Work closely with MLOps engineers to Integrate MLOps practices into the existing development lifecycle
  • Collaborate with AI Engineers, MLOps Engineers, Data Scientists and Business stakeholders to understand deployment, networking and security requirements in helping design effective AI solutions for the projects
  • Develop and test code, ensuring high quality, maintainability, and adherence to best practices.
  • Create and maintain secure and performant AI platform
  • Provide technical expertise in designing, developing and implementing the AI powered applications
  • Develop unit tests, automated regression packs and help setup model evaluation test packs
  • Build and maintain scalable, high-performance AI apps on Azure platform.
  • Provide technical expertise and support to troubleshoot and resolve AI-related issues and performance bottlenecks.
  • Stay current with industry trends and best practices in AI technology and recommend innovative solutions to enhance business operations.
  • Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
  • Document and communicate AI solutions and recommendations to technical and non-technical stakeholders clearly and effectively.
  • Develop and implement automated testing frameworks for machine learning models to ensure their ongoing accuracy and reliability.
  • Document AI development processes and procedures for efficient knowledge transfer and maintainability.


Job Deliverables


  • Developing, designing and integrating AI Powered Applications with the approved tech stack and bank standards
  • Developing Azure AI Services based AI applications
  • Creating testing frameworks, evaluating AI/ML models
  • Monitor and troubleshoot AI solutions to ensure optimal performance and address any potential issues
  • Documentation of design and implementation strategy
  • Implementation of pipeline and dependent tooling in conjunction with the clients DevOps suppliers and the clients IT Operations
  • Ensuring effective solution rollout into teams and existing applications
  • Identification of bottlenecks and performance improvements across deployment cycle
  • Help promote a AI Development best practices and culture across the client IT
  • Maintaining delivery cadence in conjunction with teams
  • Maintaining the end-to-end service delivery cycle
  • Building reusable and scalable solutions
  • Lead investigations to troubleshoot and resolve complex technical problems using a variety of techniques

Related Jobs

View all jobs

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.