425 AI Engineer jobs in the United Kingdom

We're looking for an experienced AI Consultant / Engineer to join an innovative technology team working on intelligent solutions that make a real impact. In this role, you'll use cutting-edge machine learning techniques and large language models to design, implement, and optimise AI-driven systems that enhance productivity and solve complex business problems.

If you're passionate about AI, thrive in fast-moving environments, and love building innovative solutions from scratch, this could be the perfect role for you.

• Building and refining LLM-based agents, including retrieval-augmented generation and data retrieval systems.

• Designing AI-powered system architecture using Python, Java, and SQL/NoSQL databases.

• Fine-tuning models (LLMs & SLMs) and developing machine learning applications to drive measurable results.

• Staying ahead of open-source AI trends and integrating the best tools into the tech stack.

• Prototyping, testing, and refining AI applications to improve accuracy and performance.

• Writing clean, modular Python code and performing rapid data processing and feature engineering.

• Identifying and prioritising opportunities for AI implementation based on business needs and feedback.

• Translating complex technical concepts into clear, accessible explanations for stakeholders.

Essential:

• Strong experience with Gen AI, NLP, and machine learning.

• Proven ability to create, train, and fine-tune LLMs/SLMs.

• Skills in prompt engineering and RAG (retrieval-augmented generation).

• Solid background in Python, Java, and database technologies (SQL/NoSQL).

• Experience in crawling/web scraping and API development.

• Experience with on-premise AI development (local LLMs, model deployment, open-source frameworks).

Desirable:

• Strong knowledge of data structures, algorithms, and solution architecture.

• Broad understanding of machine learning algorithms and principles.

• Salary: 60,000 - 70,000 DOE

• 25 days' annual leave + bank holidays

• Discretionary bonus scheme

• Defined contribution pension (up to 8.5% employer contribution)

• Private medical insurance & health cover options

• Flexible benefits allowance (e.g. dental, gym, travel insurance, holiday buy/sell)

• Life assurance & income protection

• Hybrid working with some on-site collaboration in Surrey

My Financial Services client is seeking to recruit a AI Engineer on an initial 6 month contract based in London. It is hybrid and will require 3x days onsite per week.

As a Back-End AI Engineer, you will design and deploy secure, scalable AI services that power next-generation use cases across client intelligence, document processing, and risk management. You'll work in a greenfield environment, building compliant AI pipelines using Gemini (GCP), Azure OpenAI or Self Hosting embedding security and privacy controls from experimentation to production, in alignment with the bank's cybersecurity and regulatory standards.

Accountabilities & Responsibilities

• Architect and implement secure AI services from lab to production, ensuring scalability and compliance
• Develop robust APIs for LLMs, RAG pipelines, agentic workflows and document intelligence systems
• Embed cybersecurity and data privacy controls across all AI workflows (e.g., encryption, anonymisation, access logging)
• Collaborate with the CISO function on threat modeling, security reviews, and AI-specific control design.
• Integrate with enterprise IAM systems, enforcing RBAC, least privilege
• Conduct vulnerability scans, pen-test remediation, and support internal and regulatory audits (FCA, PRA)

Required Knowledge & Experience

• Delivered greenfield AI systems in production with secure-by-design architecture
• Designed and managed AI lab environments using IaC, containerisation, and secure networking practices
• Hands-on experience with LLM implementation, including fine-tuning, prompt engineering, and secure deployment
• Built agentic workflows using modular LLM agents with memory, planning, and tool integration
• Implemented Model Context Protocol (MCP) to manage secure, auditable context injection across agentic systems
• Experience building RAG pipelines with strict data governance and contextual integrity
• Familiarity with EU AI Act, FCA cybersecurity principles, and oversight of critical systems
• Worked directly with cybersecurity and compliance teams in regulated deployments
• Implemented or maintained controls under ISO 27001, NIST, or SOC2 frameworks

Technical Skills & Technologies:

• Languages & Frameworks
• Python (FastAPI), LangChain, Google AI SDK, Azure Open AI SDK
• Cloud & AI Platforms
• GCP: Vertex AI, Gemini API, Cloud Run, GCS, IAM, Secret Manager, Audit Logs
• Azure: Azure ML, Azure OpenAI, Key Vault, Azure Policy
• Experience with Self Hosting
• LLM
• Fine-tuning and prompt engineering for LLMs (e.g., GPT, Gemini, Claude)
• Secure deployment of LLMs via APIs with input/output filtering and logging
• Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows
• Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval
• Implementation of grounding, context injection, and response validation mechanisms
• Model Context Protocol (MCP)
• Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual memory, grounding, and session control in LLM-based systems
• Enforce context boundary policies, context versioning, and traceability to support auditability and prevent data leakage
• Integrate MCP with enterprise IAM and data governance frameworks to ensure compliant context injection and revocation
• Agentic Workflows
• Design and orchestrate agentic AI workflows using modular, goal-driven agents with memory, planning, and tool-use capabilities
• Implement secure agent execution environments with task decomposition, tool chaining, and feedback loops
• Integrate agents with enterprise systems (e.g., document stores, APIs, risk engines) while enforcing contextual integrity, rate limiting, and audit logging
• Apply agentic patterns to automate complex financial tasks such as client onboarding, document summarisation, and risk signal extraction
• Security Tooling
• Static code analysis (Bandit, SonarQube)
• Secrets scanning, encryption (at rest/in-transit), token management
• Identity integration (Google Identity, Azure Entra ID)
• Data Security & Governance
• RAG pipelines with data classification, masking, and DLP
• GDPR and data residency compliance
• MLOps & DevSecOps
• GitHub Actions, CI/CD security testing, model drift detection, audit logging
• Lab Environment Tooling
• Infrastructure-as-Code (IaC): Terraform, Pulumi
• Containerization & Orchestration: Docker, Kubernetes (GKE/AKS)
• Networking & Isolation: VPCs, private endpoints, firewall rules, network policies
• Data Sandboxing: Synthetic datasets, masking, DLP tooling
• Monitoring & Observability: Prometheus, Grafana, Cloud Logging

Job Title: Senior AI Engineer

Location: Manchester(Hybrid)
Salary: 80,000 - 90,000 + Package
Type: Permanent, Full-Time

A market leader is looking for an experienced Senior AI Engineer to join their rapidly growing engineering team. The organisation is currently investing heavily in their Technology and Data teams as they embark on some of the most exciting AI projects currently taking place in the UK.

You will be working closely with engineers, product owners and the data team to lead some of the latest AI initiatives. As a Senior AI Engineer, you will be responsible for the design and implementation of AI systems.

You must have experience with:

Extensive experience as a Senior AI Engineer.

Strong data modelling, machine leaning and software development experience.

Knowledge of building and deploying AI/ML models.

Python

GCP preferred

Experience with Typescript and Node.js

Experience deploying models in a production environment along with natural language processing.

Mentoring and team leader experience.

Ideally experience working in a SaaS company.

You must be a team player with the ability to work in a collaborative environment.

You will be someone who is willing to learn and contribute to the wider team.

This role is perfect for a Senior AI Engineer who is looking to working on some of the latest AI projects currently in the UK.

If the role is of interest, please apply or to find out more about it please get in contact.

We are seeking a technically versatile contractor with a strong background in applied physics, data collection, and AI/ML modelling to join our team. In this role, you will bridge the gap between physical systems and data-driven models, playing a crucial role in our product testing environment.

• Design, run, and refine experiments to capture data under various test conditions.
• Structure, record, and manage datasets for machine learning training and validation.
• Analyse experimental results to extract insights and provide feedback to improve product/system performance.
• Transition an existing mechanical/physics-based model into a thermodynamic framework.
• Tune and optimise models to accurately represent real-world outcomes.
• Build and refine AI/ML models using PyTorch.
• Perform simulation and modelling work using Matlab.

• Strong grounding in thermodynamics and applied physics/engineering.
• Hands-on experience with PyTorch for machine learning.
• Proficiency in Matlab for analysis and simulation.
• Proven track record of systematic experiment design and data analysis.
• Practical mindset with the ability to work directly with hardware and real-world testing environments.
• Strong analytical and problem-solving skills.

• Previous work in food tech, IoT, or robotics.
• Familiarity with embedded systems or sensor integration.
• Exposure to fast-paced R&D or startup environments.

We're looking for an experienced AI Consultant / Engineer to join an innovative technology team working on intelligent solutions that make a real impact. In this role, you'll use cutting-edge machine learning techniques and large language models to design, implement, and optimise AI-driven systems that enhance productivity and solve complex business problems.

If you're passionate about AI, thrive in fast-moving environments, and love building innovative solutions from scratch, this could be the perfect role for you.

• Building and refining LLM-based agents, including retrieval-augmented generation and data retrieval systems.

• Designing AI-powered system architecture using Python, Java, and SQL/NoSQL databases.

• Fine-tuning models (LLMs & SLMs) and developing machine learning applications to drive measurable results.

• Staying ahead of open-source AI trends and integrating the best tools into the tech stack.

• Prototyping, testing, and refining AI applications to improve accuracy and performance.

• Writing clean, modular Python code and performing rapid data processing and feature engineering.

• Identifying and prioritising opportunities for AI implementation based on business needs and feedback.

• Translating complex technical concepts into clear, accessible explanations for stakeholders.

Essential:

• Strong experience with Gen AI, NLP, and machine learning.

• Proven ability to create, train, and fine-tune LLMs/SLMs.

• Skills in prompt engineering and RAG (retrieval-augmented generation).

• Solid background in Python, Java, and database technologies (SQL/NoSQL).

• Experience in crawling/web scraping and API development.

• Experience with on-premise AI development (local LLMs, model deployment, open-source frameworks).

Desirable:

• Strong knowledge of data structures, algorithms, and solution architecture.

• Broad understanding of machine learning algorithms and principles.

• Salary: 60,000 - 70,000 DOE

• 25 days' annual leave + bank holidays

• Discretionary bonus scheme

• Defined contribution pension (up to 8.5% employer contribution)

• Private medical insurance & health cover options

• Flexible benefits allowance (e.g. dental, gym, travel insurance, holiday buy/sell)

• Life assurance & income protection

• Hybrid working with some on-site collaboration in Surrey

My Financial Services client is seeking to recruit a AI Engineer on an initial 6 month contract based in London. It is hybrid and will require 3x days onsite per week.

As a Back-End AI Engineer, you will design and deploy secure, scalable AI services that power next-generation use cases across client intelligence, document processing, and risk management. You'll work in a greenfield environment, building compliant AI pipelines using Gemini (GCP), Azure OpenAI or Self Hosting embedding security and privacy controls from experimentation to production, in alignment with the bank's cybersecurity and regulatory standards.

Accountabilities & Responsibilities

• Architect and implement secure AI services from lab to production, ensuring scalability and compliance
• Develop robust APIs for LLMs, RAG pipelines, agentic workflows and document intelligence systems
• Embed cybersecurity and data privacy controls across all AI workflows (e.g., encryption, anonymisation, access logging)
• Collaborate with the CISO function on threat modeling, security reviews, and AI-specific control design.
• Integrate with enterprise IAM systems, enforcing RBAC, least privilege
• Conduct vulnerability scans, pen-test remediation, and support internal and regulatory audits (FCA, PRA)

Required Knowledge & Experience

• Delivered greenfield AI systems in production with secure-by-design architecture
• Designed and managed AI lab environments using IaC, containerisation, and secure networking practices
• Hands-on experience with LLM implementation, including fine-tuning, prompt engineering, and secure deployment
• Built agentic workflows using modular LLM agents with memory, planning, and tool integration
• Implemented Model Context Protocol (MCP) to manage secure, auditable context injection across agentic systems
• Experience building RAG pipelines with strict data governance and contextual integrity
• Familiarity with EU AI Act, FCA cybersecurity principles, and oversight of critical systems
• Worked directly with cybersecurity and compliance teams in regulated deployments
• Implemented or maintained controls under ISO 27001, NIST, or SOC2 frameworks

Technical Skills & Technologies:

• Languages & Frameworks
• Python (FastAPI), LangChain, Google AI SDK, Azure Open AI SDK
• Cloud & AI Platforms
• GCP: Vertex AI, Gemini API, Cloud Run, GCS, IAM, Secret Manager, Audit Logs
• Azure: Azure ML, Azure OpenAI, Key Vault, Azure Policy
• Experience with Self Hosting
• LLM
• Fine-tuning and prompt engineering for LLMs (e.g., GPT, Gemini, Claude)
• Secure deployment of LLMs via APIs with input/output filtering and logging
• Integration of LLMs into RAG pipelines, document intelligence, and agentic workflows
• Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval
• Implementation of grounding, context injection, and response validation mechanisms
• Model Context Protocol (MCP)
• Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual memory, grounding, and session control in LLM-based systems
• Enforce context boundary policies, context versioning, and traceability to support auditability and prevent data leakage
• Integrate MCP with enterprise IAM and data governance frameworks to ensure compliant context injection and revocation
• Agentic Workflows
• Design and orchestrate agentic AI workflows using modular, goal-driven agents with memory, planning, and tool-use capabilities
• Implement secure agent execution environments with task decomposition, tool chaining, and feedback loops
• Integrate agents with enterprise systems (e.g., document stores, APIs, risk engines) while enforcing contextual integrity, rate limiting, and audit logging
• Apply agentic patterns to automate complex financial tasks such as client onboarding, document summarisation, and risk signal extraction
• Security Tooling
• Static code analysis (Bandit, SonarQube)
• Secrets scanning, encryption (at rest/in-transit), token management
• Identity integration (Google Identity, Azure Entra ID)
• Data Security & Governance
• RAG pipelines with data classification, masking, and DLP
• GDPR and data residency compliance
• MLOps & DevSecOps
• GitHub Actions, CI/CD security testing, model drift detection, audit logging
• Lab Environment Tooling
• Infrastructure-as-Code (IaC): Terraform, Pulumi
• Containerization & Orchestration: Docker, Kubernetes (GKE/AKS)
• Networking & Isolation: VPCs, private endpoints, firewall rules, network policies
• Data Sandboxing: Synthetic datasets, masking, DLP tooling
• Monitoring & Observability: Prometheus, Grafana, Cloud Logging

Job Title: Senior AI Engineer

Location: Manchester(Hybrid)
Salary: 80,000 - 90,000 + Package
Type: Permanent, Full-Time

A market leader is looking for an experienced Senior AI Engineer to join their rapidly growing engineering team. The organisation is currently investing heavily in their Technology and Data teams as they embark on some of the most exciting AI projects currently taking place in the UK.

You will be working closely with engineers, product owners and the data team to lead some of the latest AI initiatives. As a Senior AI Engineer, you will be responsible for the design and implementation of AI systems.

You must have experience with:

Extensive experience as a Senior AI Engineer.

Strong data modelling, machine leaning and software development experience.

Knowledge of building and deploying AI/ML models.

Python

GCP preferred

Experience with Typescript and Node.js

Experience deploying models in a production environment along with natural language processing.

Mentoring and team leader experience.

Ideally experience working in a SaaS company.

You must be a team player with the ability to work in a collaborative environment.

You will be someone who is willing to learn and contribute to the wider team.

This role is perfect for a Senior AI Engineer who is looking to working on some of the latest AI projects currently in the UK.

If the role is of interest, please apply or to find out more about it please get in contact.

AI Engineer - LLMs for Document Intelligence | Remote (UK) | Up to £70,000

We're supporting a UK-based SaaS company in hiring an AI Engineer to join their Innovation team. This role is focused on delivering real business impact through Generative AI, particularly in the area of document intelligence.

The opportunity

• Build and deploy LLM-based systems to automate document extraction, reasoning and validation
• Work on high-impact use cases, such as ESG and sustainability compliance
• Join a small, collaborative team that values clean code, fast iteration and practical AI solutions

What you'll do

• Design and implement LLM-powered workflows for document understanding, including RAG and agent-based systems
• Develop robust, well-structured Python libraries and production-ready services
• Build quick prototypes (Streamlit, Dash) and scalable services (FastAPI, Kubernetes)
• Contribute to engineering best practices across CI/CD, testing, and monitoring

What we're looking for

• Previous experience with document extraction using LLMs
• Expert-level Python skills, with a strong grounding in software engineering fundamentals
• Clear communicator, comfortable working with both technical and non-technical stakeholders

What's on offer

• Up to £70,000 base salary
• Remote-first working culture (UK only)
• Company offsites across Europe
• Private medical insurance, life assurance and pension
• 25 days holiday plus bank holidays, with the option to buy more
• Wellness and professional development budgets

2 stage interview process.

This role cannot sponsor and ideally candidates will have 1 month or less notice period, aiming for a September/early October start.

AI Engineer - Remote

We're hiring an AI Engineer to help design and build cutting-edge AI solutions with a focus on document intelligence. You'll play a key role in embedding GenAI across the business, starting with tools to support verification teams in extracting and reasoning over complex documents.

This is a hands-on engineering role with a strong focus on LLM-based systems and clean, production-grade Python development.

Responsibilities:

• Build rapid MVPs and evolve them into production-ready services.
• Develop and maintain shared Python libraries with strong architecture, testing, and CI/CD standards.
• Design and deploy LLM-based extraction, RAG, and agent workflows across large document sets.
• Work closely with both technical and non-technical stakeholders.

Required:

• Expert in Python coding
• Solid grounding in software engineering best practices: CI/CD, automated testing, observability.
• Experience with multi-modal AI (e.g. layout understanding, VLMs, agentic workflows).
• Comfortable prototyping quickly (Streamlit, Dash) to test ideas.
• Familiar with MLOps tools like MLflow and model monitoring.
• Strong communicator who can work across teams.