AI Engineer Salary: up to £65,000 Location: UK based - Midlands preferred, but remote considered Type: Permanent I'm working with a growing fintech/scale-up that is building AI into a customer-facing product used within the affordability and financial services space. They already have an AI virtual assistant within the platform, but until now a lot of the specialist AI work has sat with an external partner. They've reached the point where they want to start bringing that capability in-house and are looking for someone who can help them build on what is already there. This is not a role for someone who wants to train their own LLM from scratch. It is more about taking existing LLMs and AI services, understanding how to use them properly, and building useful product features around them. The business is fairly open-minded on level. You might be a graduate with a year or two of experience, a Python developer who has started moving into AI, a Machine Learning Engineer, or a Data Scientist with stronger engineering habits. They are not expecting someone to have ten years of LLM experience, because realistically very few people do. What they do need is someone bright, practical and genuinely interested in building AI that works in the real world. You'll be working on the AI side of a product that helps users complete income and expenditure journeys. In simple terms, the customer can either fill in the form themselves, or interact with the virtual assistant, which helps capture and complete the information for them. That means the AI work has to fit into a wider software product. It needs to connect with the front end, work safely, be tested properly, and be built with security in mind from the start. The role will involve: Building and improving AI/LLM features using Python Creating quick proof of concepts to test ideas Taking the right ideas further into production Working with existing LLMs, APIs and AI services Thinking about guardrails, safety, hallucination risk and validation Building software in a secure way, particularly given the regulated nature of the product Supporting automated testing rather than treating testing as an afterthought Working in a DevOps environment where builds, releases and deployments are automated Understanding how the AI module fits into the wider product and customer journey The key things they are looking for are: Strong Python skills A good general understanding of LLMs Some exposure to GenAI, chatbots, NLP, RAG, prompt engineering or similar An interest in AI guardrails and responsible use of AI Good software engineering principles Awareness of security in modern development A willingness to test properly and automate where possible Some understanding of cloud platforms - Azure would be ideal, but AWS or GCP is fine The ability to learn quickly and work out the right way to use new technologies It would also be useful if you had experience with JavaScript, deep learning, LangChain, LlamaIndex, Azure OpenAI, OpenAI APIs or similar tools, but none of these are absolute requirements. This is probably best suited to someone who wants more ownership than they may get in a larger business. You'll be close to senior technology leadership, close to the product, and involved in shaping how AI is used rather than just being handed small pieces of work. The most important thing is mindset. They want someone who can build, test, learn quickly, and stay focused on why the feature is being built in the first place.
May 20, 2026
Full time
AI Engineer Salary: up to £65,000 Location: UK based - Midlands preferred, but remote considered Type: Permanent I'm working with a growing fintech/scale-up that is building AI into a customer-facing product used within the affordability and financial services space. They already have an AI virtual assistant within the platform, but until now a lot of the specialist AI work has sat with an external partner. They've reached the point where they want to start bringing that capability in-house and are looking for someone who can help them build on what is already there. This is not a role for someone who wants to train their own LLM from scratch. It is more about taking existing LLMs and AI services, understanding how to use them properly, and building useful product features around them. The business is fairly open-minded on level. You might be a graduate with a year or two of experience, a Python developer who has started moving into AI, a Machine Learning Engineer, or a Data Scientist with stronger engineering habits. They are not expecting someone to have ten years of LLM experience, because realistically very few people do. What they do need is someone bright, practical and genuinely interested in building AI that works in the real world. You'll be working on the AI side of a product that helps users complete income and expenditure journeys. In simple terms, the customer can either fill in the form themselves, or interact with the virtual assistant, which helps capture and complete the information for them. That means the AI work has to fit into a wider software product. It needs to connect with the front end, work safely, be tested properly, and be built with security in mind from the start. The role will involve: Building and improving AI/LLM features using Python Creating quick proof of concepts to test ideas Taking the right ideas further into production Working with existing LLMs, APIs and AI services Thinking about guardrails, safety, hallucination risk and validation Building software in a secure way, particularly given the regulated nature of the product Supporting automated testing rather than treating testing as an afterthought Working in a DevOps environment where builds, releases and deployments are automated Understanding how the AI module fits into the wider product and customer journey The key things they are looking for are: Strong Python skills A good general understanding of LLMs Some exposure to GenAI, chatbots, NLP, RAG, prompt engineering or similar An interest in AI guardrails and responsible use of AI Good software engineering principles Awareness of security in modern development A willingness to test properly and automate where possible Some understanding of cloud platforms - Azure would be ideal, but AWS or GCP is fine The ability to learn quickly and work out the right way to use new technologies It would also be useful if you had experience with JavaScript, deep learning, LangChain, LlamaIndex, Azure OpenAI, OpenAI APIs or similar tools, but none of these are absolute requirements. This is probably best suited to someone who wants more ownership than they may get in a larger business. You'll be close to senior technology leadership, close to the product, and involved in shaping how AI is used rather than just being handed small pieces of work. The most important thing is mindset. They want someone who can build, test, learn quickly, and stay focused on why the feature is being built in the first place.
AI Implementation Engineer - Manchester A growing technology-led business is looking to hire an AI Implementation Engineer to help drive practical AI adoption across multiple areas of the organisation. This is a hands-on role focused on delivering AI solutions from concept through to live deployment and business adoption. Working within IT and closely alongside operational and commercial teams, you will build and implement practical AI use cases using Azure, LLMs, machine learning, and AI agents - ensuring solutions are secure, integrated, scalable, and actively used across the business. The organisation is already exploring a broad range of AI initiatives and is looking for someone capable of getting hands-on with implementation, working collaboratively with existing technical teams, and helping shape the future AI capability of the business. This role would suit someone who enjoys building practical AI solutions, solving operational problems, and delivering measurable business impact in a fast-moving environment. Role Purpose Hands-on role responsible for delivering AI solutions from concept through to live deployment and business adoption. Working within IT and closely with business teams, you will build and implement practical AI use cases using Azure, LLMs, ML, and AI agents ensuring they are secure, integrated, scalable, and actively used. Key Responsibilities Design and build high-performing AI models tailored to specific business needs Lead rapid prototyping initiatives through to production delivery Work directly with the IT Infrastructure team to deploy AI models into production environments Ensure solutions use Private Endpoints and meet enterprise-grade security standards Work with operational and business teams to embed AI tools into day-to-day workflows Drive adoption and ensure teams are actively using implemented AI solutions Set up automated evaluation and monitoring frameworks for production AI environments, including hallucination detection, drift monitoring, and latency tracking (GenAIOps) Ensure AI solutions integrate securely with existing systems, data platforms, and APIs Collaborate with commercial stakeholders to assess project viability and business value before implementation Measure and track project impact, including efficiency gains, time savings, automation improvements, and quality outcomes Work closely with IT, development, and leadership teams to identify and prioritise AI opportunities across the organisation Required Experience Essential Deep expertise in Python and relevant AI/ML frameworks and SDKs Proven experience building RAG pipelines that operate effectively in production environments Hands-on experience with model packaging, deployment, and production AI workflows Strong understanding of enterprise infrastructure concepts including VNets, Entra ID, API Gateways, and secure integrations Experience working with at least one major enterprise AI cloud platform (Azure preferred) Strong SQL skills and experience working with both structured and unstructured data Experience building AI agents, workflow automation, and tool/API integrations Strong understanding of AI implementation, deployment, and operationalisation Ability to work closely with technical and non-technical stakeholders Strong problem-solving and communication skills Desirable Experience with LLMOps / GenAIOps tooling and monitoring frameworks Exposure to OCR, computer vision, voice AI, or conversational AI solutions Experience working in operational, retail, automotive, or customer-focused businesses Familiarity with AI governance, security, and scalability best practices Experience helping shape or build internal AI capabilities within a business Salary & Benefits Competitive salary depending on experience Quarterly bonus scheme Hybrid working arrangements 3 days office / 2 days remote Opportunity to shape AI capability within a growing business Strong long-term career progression opportunities Interested? Please click Apply Now! AI Implementation Engineer - Manchester
May 20, 2026
Full time
AI Implementation Engineer - Manchester A growing technology-led business is looking to hire an AI Implementation Engineer to help drive practical AI adoption across multiple areas of the organisation. This is a hands-on role focused on delivering AI solutions from concept through to live deployment and business adoption. Working within IT and closely alongside operational and commercial teams, you will build and implement practical AI use cases using Azure, LLMs, machine learning, and AI agents - ensuring solutions are secure, integrated, scalable, and actively used across the business. The organisation is already exploring a broad range of AI initiatives and is looking for someone capable of getting hands-on with implementation, working collaboratively with existing technical teams, and helping shape the future AI capability of the business. This role would suit someone who enjoys building practical AI solutions, solving operational problems, and delivering measurable business impact in a fast-moving environment. Role Purpose Hands-on role responsible for delivering AI solutions from concept through to live deployment and business adoption. Working within IT and closely with business teams, you will build and implement practical AI use cases using Azure, LLMs, ML, and AI agents ensuring they are secure, integrated, scalable, and actively used. Key Responsibilities Design and build high-performing AI models tailored to specific business needs Lead rapid prototyping initiatives through to production delivery Work directly with the IT Infrastructure team to deploy AI models into production environments Ensure solutions use Private Endpoints and meet enterprise-grade security standards Work with operational and business teams to embed AI tools into day-to-day workflows Drive adoption and ensure teams are actively using implemented AI solutions Set up automated evaluation and monitoring frameworks for production AI environments, including hallucination detection, drift monitoring, and latency tracking (GenAIOps) Ensure AI solutions integrate securely with existing systems, data platforms, and APIs Collaborate with commercial stakeholders to assess project viability and business value before implementation Measure and track project impact, including efficiency gains, time savings, automation improvements, and quality outcomes Work closely with IT, development, and leadership teams to identify and prioritise AI opportunities across the organisation Required Experience Essential Deep expertise in Python and relevant AI/ML frameworks and SDKs Proven experience building RAG pipelines that operate effectively in production environments Hands-on experience with model packaging, deployment, and production AI workflows Strong understanding of enterprise infrastructure concepts including VNets, Entra ID, API Gateways, and secure integrations Experience working with at least one major enterprise AI cloud platform (Azure preferred) Strong SQL skills and experience working with both structured and unstructured data Experience building AI agents, workflow automation, and tool/API integrations Strong understanding of AI implementation, deployment, and operationalisation Ability to work closely with technical and non-technical stakeholders Strong problem-solving and communication skills Desirable Experience with LLMOps / GenAIOps tooling and monitoring frameworks Exposure to OCR, computer vision, voice AI, or conversational AI solutions Experience working in operational, retail, automotive, or customer-focused businesses Familiarity with AI governance, security, and scalability best practices Experience helping shape or build internal AI capabilities within a business Salary & Benefits Competitive salary depending on experience Quarterly bonus scheme Hybrid working arrangements 3 days office / 2 days remote Opportunity to shape AI capability within a growing business Strong long-term career progression opportunities Interested? Please click Apply Now! AI Implementation Engineer - Manchester
AI Technical Architect 6 Months Remote Contract 600 a day Inside IR35 Active Security Check (SC) Clearance is needed for this role A well-established IT solution provider is looking for an experienced AI Technical Architect to join an existing team of experts. In this highly visible role, you will act as the bridge between complex data science and robust cloud architecture-spearheading the design, governance, and delivery of enterprise-grade AI solutions. You will technically steer engineering teams, manage senior stakeholder relationships, and deliver production-ready Generative AI capabilities. The ideal candidate must be heavily hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across the delivery lifecycle. GenAI & LLM Engineering: Take a hands-on approach to deploying, fine-tuning, and customising pretrained LLMs. Build intelligent systems utilising Prompt Engineering, Vector Databases, Azure OpenAI, and Cognitive Search. Data Pipelines: Oversee large-scale data processing and AI data engineering pipelines using Python and PySpark. Leadership & Stakeholder Management: Guide and mentor engineering teams while confidently managing client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks for production deployment. 6 Months Remote Contract 600 a day inside IR35 Active Security Clearance Are you a seasoned technical leader with a passion for cutting-edge artificial intelligence? If this sounds like your next challenge, please apply directly to this advert or send your CV to (url removed). Randstad Technologies is acting as an Employment Business in relation to this vacancy.
May 17, 2026
Contractor
AI Technical Architect 6 Months Remote Contract 600 a day Inside IR35 Active Security Check (SC) Clearance is needed for this role A well-established IT solution provider is looking for an experienced AI Technical Architect to join an existing team of experts. In this highly visible role, you will act as the bridge between complex data science and robust cloud architecture-spearheading the design, governance, and delivery of enterprise-grade AI solutions. You will technically steer engineering teams, manage senior stakeholder relationships, and deliver production-ready Generative AI capabilities. The ideal candidate must be heavily hands-on with Python and Azure , possessing a proven track record of designing and deploying Retrieval-Augmented Generation (RAG) patterns. Key Responsibilities Architect & Govern: Design and implement robust on-premises, cloud, and hybrid AI solutions, ensuring strict technical governance and best practices across the delivery lifecycle. GenAI & LLM Engineering: Take a hands-on approach to deploying, fine-tuning, and customising pretrained LLMs. Build intelligent systems utilising Prompt Engineering, Vector Databases, Azure OpenAI, and Cognitive Search. Data Pipelines: Oversee large-scale data processing and AI data engineering pipelines using Python and PySpark. Leadership & Stakeholder Management: Guide and mentor engineering teams while confidently managing client relationships to secure consensus on complex technical architectures. Essential Skills Clearance: Active UK Government Security Check (SC). GenAI: Expertise in LLMs and RAG architectures. Python: Strong proficiency alongside PySpark for data engineering. Azure: Deep familiarity with native tools (AI Search, Document Intelligence). MLOps: Understanding of LLMOps frameworks for production deployment. 6 Months Remote Contract 600 a day inside IR35 Active Security Clearance Are you a seasoned technical leader with a passion for cutting-edge artificial intelligence? If this sounds like your next challenge, please apply directly to this advert or send your CV to (url removed). Randstad Technologies is acting as an Employment Business in relation to this vacancy.
