7 jobs found

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

Insurance Technical Specialist (Broking/Actuarial) - Contract - £650/pd Please note - this role will require you to attend the Central London office 2-3 days per week. You must have the unrestricted right to work in the UK to be eligible for this role. This organisation is not able to offer sponsorship. I am working with my London Market broker client, an innovative brokerage pushing beyond traditional operating models by combining deep market expertise with emerging AI and modern engineering practices. They are seeking an Insurance Technical Specialist for a broker-side change initiative, aimed at shaping and delivering new capabilities for the London Market. This role is deliberately hybrid: it suits someone with extensive insurance broking experience or an actuarial background, who can also "vibe code" - rapidly prototyping, configuring, and iterating solutions using modern low-friction development approaches and AI-assisted tooling. The Opportunity This is a hands-on contract role sitting between business, data, and technology. You will apply your deep understanding of insurance and market mechanics while actively contributing to solution design and build. The work supports a broader strategy to leverage AI-driven insight, automation, and decision support, enabling the broker to bring something genuinely new to the London Market. Key Responsibilities Act as a technical insurance SME across broking and/or actuarial domains Translate complex insurance concepts into functional and technical artefacts Rapidly prototype and iterate solutions using vibe coding / AI-assisted development techniques Support data-driven and AI-enabled use cases across broking, placement, pricing, or analytics Work closely with data architects, engineers, and delivery teams to ensure solutions reflect real market behaviour Validate outputs against London Market practices, regulatory expectations, and broker operating models Contribute to defining how insurance logic is embedded into systems, models, and workflows Required Experience Extensive experience in insurance broking or a strong actuarial background Deep knowledge of London Market structures, processes, and products Proven ability to operate as a hands-on technical specialist, not just advisory Experience using modern coding, scripting, or prototyping approaches Comfortable experimenting, iterating, and building alongside delivery teams Strong stakeholder engagement skills across business and technology audiences Highly Desirable Experience applying AI, machine learning, or advanced analytics in an insurance context Exposure to modern data platforms, APIs, or cloud-based environments Experience working in transformation or innovation-led broker initiatives This is a 6 month engagement which offers £650/pd Outside IR35. To apply for this role please submit your CV or contact David Airey on or at . Tenth Revolution Group are the go-to recruiter for Data & AI roles in the UK offering more opportunities across the country than any other recruitment agency. We're the proud sponsor and supporter of SQLBits, Power Platform World Tour, and the London Fabric User Group. We are the global leaders in Data & AI recruitment.

Qualification Type: PhD Location: Manchester - UK Funding for: UK and International Funding amount: £21,805 per annum Start date: September 2026 Hours: Full Time Closes: 29 May 2026 (midnight) PhD by Enterprise (Alliance Manchester Business School) The University of Manchester's PhD by Enterprise is a new four year doctoral programme that combines world class research with structured entrepreneurship training. The programme enables the University's research portfolio to generate tangible economic, environmental and societal impact through venture creation and enterprise-led pathways. The programme includes a fully funded studentship to commence in September 2026, covering tuition fees, UKRI stipend (2026/27 rate £21,805 per annum) and Research Training Support Grant. You will be based in the Alliance Manchester Business School at The University of Manchester, a top 5 UK business school (QS World University Rankings 2026). Project details: AIDE: Agentic Intelligence for Decision-making in Investment and Enterprise Investment and venture evaluation environments, such as venture capital, private equity, and university innovation ecosystems, are becoming increasingly data intensive. Yet despite the abundance of available information, decision-making across deal sourcing, evaluation, due diligence, and post investment monitoring remains fragmented and highly manual. Current commercial platforms excel at search and data aggregation, but they provide limited support for deeper reasoning, scenario exploration, or coordinated, lifecycle wide decision support. This PhD project, AIDE: Agentic Intelligence for Decision-making in Investment and Enterprise, aims to address these challenges by developing next-generation AI systems capable of supporting holistic, data-driven and uncertainty-aware decision-making. Based in the prestigious Alliance Manchester Business School, the project will also explore the design and development of knowledge graphs to structure and connect heterogeneous data sources, enabling richer contextual understanding and reasoning. The project offers an exciting opportunity to work at the frontier of applied AI, decision sciences, and real-world innovation ecosystems, advancing new research while contributing to a potential future commercial venture. A central ambition of the project is to build AI systems that are not only powerful, but also explainable. Investment decisions are high-stakes, and users must be able to understand why the system recommends particular actions or highlights certain risks. The PhD will explore explainable AI (XAI) methods that enable transparency, interpretability and user trust, ensuring that recommendations can be interrogated, justified, and adapted by human experts. This includes surfacing the key evidence, assumptions, and uncertainties underpinning each step of the decision process, potentially leveraging knowledge graph structures to trace relationships and reasoning paths across data. The research will investigate how diverse information sources, such as structured financial data, textual documents, company disclosures, and online signals, can be integrated into unified representations that support robust reasoning, including the construction and utilisation of knowledge graphs for entity linking, relationship modelling, and semantic integration. Equally important is modelling uncertainty: decision-makers often work with incomplete, noisy or fast-changing data. The project will examine techniques for quantifying and propagating uncertainty across multi-stage workflows, enabling users to explore how assumptions or market changes affect potential outcomes. The student will also study how multiple AI agents can collaborate to reflect real-world investment workflows, coordinating tasks such as screening, due-diligence analysis, risk assessment and scenario modelling, with knowledge graphs potentially serving as a shared structured memory and coordination layer across agents. The design will emphasise human-AI collaboration, ensuring users retain oversight, agency, and the ability to challenge or override recommendations. Methodologically, the project blends machine learning, probabilistic modelling, multi-agent systems, explainable AI, and human-computer interaction, alongside knowledge representation and graph-based reasoning techniques. A design-science research approach will be used, with iterative prototyping, evaluation using realistic scenarios, and engagements with practitioners from investment and innovation communities. Academic Criteria: Bachelor's (Honours) degree at 2:1 or above (or overseas equivalent); and Master's degree in a relevant cognate subject normally with an overall average of 65% or above (or equivalent) Professional qualifications and/or relevant and appropriate experience. Desirable Criteria: A degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Statistics, Mathematics, Engineering, Information Systems, or a closely related discipline. A Master's degree in one of the above areas. Strong analytical and programming skills (e.g., Python, machine learning frameworks) are advantageous, alongside an interest in applied AI, decision making systems, and explainable or uncertainty aware modelling. Candidates from numerate disciplines with professional experience in data science, analytics, financial technology, investment analysis, or innovation ecosystems are also encouraged. Crucially, applicants should be motivated to conduct high quality research at the intersection of AI and real world enterprise applications, with an interest in developing transparent, explainable and user centred decision support technologies. English Language Evidence: IELTS minimum scores - 7.0 overall, 6.5 other sections. Other tests may be considered. TOEFL (internet based) test minimum scores - 100 overall, 25 in all sections. Pearson Test of English (PTE) UKVI/SELT or PTE Academic minimum scores - 76 overall, 76 in writing, 70 in other sections. To demonstrate that you have taken an undergraduate or postgraduate degree in a majority English speaking nation within the last 5 years. Other tests may be considered. The application deadline will be 11:59PM (GMT) on 29/05/26. Apply online for 'PhD by Enterprise HUMS'. If you would like to discuss the project further, contact Prof Richard Allmendinger ()

Software Developer - SC cleared Permanent Hybrid (willing to travel to Newcastle) Python AI BPSS We are looking for Software Developers with strong Python and AI experience to work at an early stage alongside enterprise architects and senior engineers. You will help research, design and prototype the foundations of a new service, with particular emphasis on automation, integration and intelligent workflows. You will join Peregrine who are supporting a large public sector organisation, starting an ambitious transformation programme focused on modernising how financial support services are delivered. The aim is to explore whether multiple existing approaches can be consolidated into a single, streamlined service. This work is at Alpha stage, with a strong focus on research, prototyping and proving technical and architectural options. This is a hands-on role suited to engineers who enjoy shaping solutions from first principles and working in exploratory delivery phases. The role is primarily remote, however travel to Newcastle may be required for sprint ceremonies and key workshops. Responsibilities: Engineers will contribute to research and development across: Workflow orchestration and process design Web portal options and user interaction patterns Data models and schema design Automation and AI, including AI assisted software development approaches Skills & Experience: Strong experience with Python Experience applying AI or machine learning in practical solutions Focus on automation and system integration Comfortable working in early stage, fast evolving environments (Alpha project experience) AWS Services Active BPSS, SC clearance or eligible for clearance Desirable skills: Experience supporting AI or data driven platforms Knowledge of cyber security or fraud prevention domains Experience working within government or critical national infrastructure environments About Peregrine We build workforces that deliver tech and change programmes at leading UK organisations. By combining data science from Peregrine Intelligence, our industry-accredited Peregrine Academy, and market-leading attraction and diversity initiatives, we bridge capability gaps at all levels in public and private sector organisations. We work closely with our clients to understand their challenges and deliver flexible, long-term solutions that make a real difference. When you join Peregrine, you become part of a team that s focused on growth, both yours, our clients , and the sectors we support. You ll also get access to a full range of benefits alongside your salary. How Specialist Talent Works As a permanent employee at Peregrine, you ll be part of our Specialist Talent team. That means you ll work on-site or remotely with our clients, supporting them on complex, high-impact projects in Data, Digital and Business Transformation. You ll get the variety and challenge of consultancy work, with the stability and support of a permanent role. You re not a contractor - you re a valued member of our team, with access to all the same benefits, learning opportunities, and community. Find out more: peregrine.global or check out our LinkedIn page: peregrine-resourcing

We are seeking a detail-oriented and technically skilled AI & Data Process Intelligence Analyst with 3+ years of experience in automation and intelligent process improvement. In this role, you will design, develop, and deploy AI-enabled automation solutions, leverage process mining techniques to identify optimisation opportunities, and apply data-driven insights to enhance operational efficiency across the business. This position sits at the intersection of automation, data analysis, and applied machine learning. You will work closely with business stakeholders to deliver scalable and practical solutions. Key Responsibilities Apply AI and automation techniques to streamline and improve operational processes. Develop dashboards and performance reports using Power BI to support data-driven decision making. Use prototyping and design tools (e.g. Google Gravity, Figma Make) to design, document, and optimise process workflows and automation solutions. Build and integrate machine learning models (e.g. classification, prediction, and optimisation) into automation workflows where appropriate. Analyse structured and unstructured data using Python and SQL to validate business problems and quantify potential process improvements. Collect, clean, and prepare operational data from multiple sources for analysis and modelling. Collaborate with business stakeholders to gather requirements and translate them into scalable automation and AI solutions. Monitor deployed automations and AI models to ensure ongoing performance, accuracy, and reliability. Document solutions, maintain governance standards, and adhere to best practices for automation lifecycle management. Required Experience & Skills 3+ years of experience in automation engineering, intelligent process automation, AI/ML implementation, digital transformation, or a similar technical role. Strong proficiency in Python and SQL for data analysis and automation development. Hands-on experience with RPA and workflow automation tools (e.g. Power Automate, UiPath). Practical experience developing and deploying machine learning models in Python (e.g. scikit-learn, pandas). Experience working with APIs and integrating systems across business platforms. Strong analytical thinking and problem-solving skills with the ability to translate complex data into actionable insights.

AI Engineer Our client, a leading global supplier for IT services, requires an experienced AI Engineer to be based at their client's office in Sheffield, UK. This is a hybrid role - you can work remotely in the UK and attend the Sheffield office 2 days per week . This is a 6+ month temporary contract to start ASAP Day rate: Competitive Market rate This position falls under the client's Group Data Technology space. The key focus is on creating connections between business processes, data, products, services, and technology that underpin customer interactions and drive financial success. The team provides a single comprehensive data cataloguing solution across multiple business units. Key Responsibilities Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training, and defining support procedures, in collaboration with an advanced engineering team and executive leadership Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation Conduct assessments of the AI for a given use case and come up with recommendations and alternate ways to achieve the objectives Key Requirements Essential: Proven experience of Chat Bot development using below listed technologies (Mandatory) Python, PyCharm, Numpy, Pandas Experience with ML, deep learning, TensorFlow, Python, NLP MySQL, PostgreSQL, NoSQL, RDBMS design and modelling GitHub, Jenkins Data modelling, Data wrangling and extraction Experience in developing classification algorithms and data preparation Must have experience in either one or more of the expertise areas like Image processing, text extraction, clustering, classification and embedding models Must have experience on developing Drift detection and Model monitoring implementation, good to have experience with AgentEvals for Large Language Models Desirable: Bachelor's degree or higher in computer science, engineering or related field 5-7 years of experience in architecting, positioning and delivering data science and machine learning Experience with Supervised and Unsupervised learning algorithms, good to have experience on Classification algorithms Experience with Document Type classifier, Pattern matching and PII identification Hands on experience in model training, drift detection and feature generation Expertise in Agile and can work with at least one of the common frameworks Ability to identify network attacks and systemic security issues as they relate to threats and vulnerabilities, with focus on recommendations for enhancements or remediation Dev-ops and application security & data security experience Securing highly available Internet banking application Knowledge of client side applications and micro services architecture Excellent written and spoken communication skills; an ability to communicate with impact, ensuring complex information is articulated in a meaningful way to wide and varied audiences Build effective networks across business areas, developing relationships based on mutual trust and encouraging others to do the same Ability to quickly acquire new skills and tools Good To Have Skills: Computer Vision problem solution, Advanced pattern matching PII identification and extraction Document type classifiers Standardised form matcher 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.

Senior Machine Learning Engineer - Behavioural Modeling & Threat Detection - £150,000 - £180,000 - Fully Remote UK BASED CANDIDATES ONLY My client is looking for an experienced Machine Learning Engineer ready to play a pivotal role in shaping the technical direction of their behavioural modelling and threat detection systems. This position offers the opportunity to influence not just their engineering roadmap, but how they fundamentally approach solving complex, real-world security challenges with data. You'll work at the intersection of data science, ML infrastructure, and product innovation, leading efforts to build and evolve ML-driven capabilities, while also ensuring the reliability and scalability of their models in production environments. What You'll Do Spearhead the design and refinement of machine learning models focused on understanding behaviour patterns and identifying cybersecurity anomalies. Partner with product, engineering, and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy with tactical improvements. Champion code quality, observability, and resilience within their ML systems through reviews and hands-on contributions. Help shape their internal ML standards and practices, ensuring they stay ahead of industry advancements. Offer technical mentorship and be a thought partner to colleagues across data, ML, and engineering disciplines. What We're Looking For Hands-on experience in developing and deploying machine learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data tools (Spark, etc.). Strong written and verbal communication skills, especially in cross-functional contexts. Bonus Experience (Nice to Have) Exposure to large language models (LLMs) or foundational model adaptation. Previous work in cybersecurity, anomaly detection, or behavioural analytics. Familiarity with orchestration frameworks (Airflow or similar). Experience with scalable ML systems, pipelines, or real-time data processing. Advanced degree or equivalent experience in ML/AI research or applied science. Cloud platform proficiency (AWS, GCP, Azure). If this sounds like something you would be interested in, please apply with your latest CV, a number to reach you on and I will be in touch. Alternatively, you can email me at . RSG Plc is acting as an Employment Agency in relation to this vacancy.