24 jobs found

AI Architect (Generative & Agentic AI) Permanent Location: London (onsite twice a week) Salary: £80,000 - £95,000 Per Annum D.O.E Plus benefits & Bonus Shape the next generation of enterprise AI We're looking for a senior AI Architect to lead the design and delivery of cutting-edge Generative and Agentic AI solutions across complex enterprise environments. This is a client-facing, strategic role for someone who combines deep technical expertise with strong consulting instincts, someone who can move comfortably between vision, architecture, and real-world delivery. You'll work on high-value transformation initiatives, helping organisations turn AI from experimentation into measurable business impact. The Role: As an AI Architect, you'll operate at the intersection of strategy, solution design, and delivery. You will: Lead discovery and design of AI-led solutions aligned to business outcomes Architect and scale GenAI, RAG, and Agentic AI systems in production Advise senior stakeholders on AI strategy, feasibility, and roadmap Act as a technical authority during bids, proposals, and client workshops Guide engineering teams through complex implementations This role offers real ownership, from shaping ideas through to deploying production-grade AI platforms. Key Responsibilities: Client & Stakeholder Engagement Partner with commercial and delivery teams to qualify opportunities and shape compelling AI propositions Act as a trusted advisor in workshops, discovery sessions, and solution design discussions Support RFI/RFP responses and client presentations with clear, credible technical direction Solution Architecture & Delivery Design enterprise-ready Data & AI architectures using modern cloud platforms (AWS, Azure, GCP) Architect RAG-based GenAI solutions, chatbots, and autonomous/agentic workflows Select appropriate models, frameworks, orchestration tools, and evaluation approaches Ensure solutions are secure, scalable, observable, and production-ready Technical Leadership & Innovation Lead and mentor teams of AI and software engineers Drive best practices across MLOps / LLMOps, governance, and AI observability Contribute to reusable accelerators, reference architectures, and go-to-market offerings What We're Looking For: Essential Experience & Skills: Proven experience architecting solutions across Generative AI, Agentic AI, ML, and automation Strong understanding of: Prompt engineering RAG pipelines Model fine-tuning (supervised / unsupervised) MLOps / LLMOps and AI observability Hands-on experience building enterprise RAG solutions using LLMs (e.g. OpenAI, Llama, Mistral, Claude) and vector databases (Pinecone, Weaviate, FAISS, etc.) Practical experience with GenAI frameworks such as LangChain, LlamaIndex, and agentic frameworks like AutoGen, CrewAI, LangGraph Strong Python expertise with AI/ML frameworks (PyTorch, TensorFlow) and NLP libraries Experience deploying AI solutions on at least one major cloud platform (AWS, Azure, or GCP) Solid software engineering foundations for building scalable, maintainable systems Experience leading or guiding teams of AI / software engineers Consulting & Communication: Strong stakeholder management and communication skills Comfortable translating complex AI concepts into clear business value Experience supporting proposals, bids, and client presentations Why Apply? Work on meaningful, enterprise-scale AI transformation programmes Shape AI strategy and architecture, not just build proofs of concept High visibility, senior-level role with real influence Continuous exposure to modern AI tooling, frameworks, and delivery models Strong investment in learning, innovation, and professional development

At Morrisons, our Data, Analytics & AI team plays a vital role in driving decisions across the business by unlocking the power of our data. Whether it's enabling quick insight through self-serve tools like Looker or delivering deeper analysis through exploring the patterns in our data, we help teams across the business solve problems, drive performance, and create value. As a Data Science Manager, you'll lead a small but impactful team of data scientists and analysts, helping shape and deliver a roadmap of data science products and initiatives that align with our business goals. You'll work closely with stakeholders across the organisation to understand their challenges and apply cutting-edge analytics to solve them. This is a hands on role with technical delivery at its core, combined with leadership and strategic direction. What you'll be doing: Lead, mentor and develop a team of Data Scientists and Analysts, setting clear objectives and supporting professional growth Own the delivery of complex data science products and models that support strategic business objectives Shape and contribute to a 1-2 year data science roadmap, ensuring all work is aligned with business priorities and linked to core processes Embed a lean, value first culture, minimising waste and driving improvements in efficiency and EBITDA Champion data literacy and promote best practice in analytical thinking across the business Translate business problems into analytical approaches, delivering insights that inform action Support the team with hands on technical tasks where required, including coding and modelling Collaborate with Data Engineering and other teams to ensure the right data is available and accessible About you What we're looking for: A strategic thinker with experience solving complex business problems through data Strong communication and storytelling skills. Able to bring data to life for non technical audiences An inclusive and motivating leader, with experience mentoring others and creating high performing teams Comfortable working in both Agile and Waterfall environments Inquisitive mindset - always looking to challenge the status quo and improve ways of working Excellent stakeholder management skills, with the ability to gather and refine requirements to ensure value delivery Key Skills: Expert level SQL skills, extracting and transforming data with speed and accuracy Strong programming experience (preferably Python or R), with experience of building, testing and deploying machine learning models Experience delivering predictive or prescriptive models into production, with knowledge of current MLOps principles Skilled in creating impactful data visualisations and dashboards Working knowledge of cloud platforms such as GCP or AWS, with Google preferred About us In return for all your hard work, you will receive: 15% discount in store from the day you join us Additional 10% discount card for a friend or family member Annual bonus scheme Career progression and development opportunities Generous holiday entitlement Market leading pension scheme and life assurance Healthcare benefits including Aviva Digital GP 'MyPerks' giving you discount with over 850 retailers Free parking onsite Enhanced Family, Maternity and Paternity Leave Private Healthcare Car Allowance (company car provided in some instances) Alive with activity, our modern Head Office is home to our corporate teams that make sure everything runs smoothly. Here, you'll find comfy breakout areas, a coffee shop, Morrisons Daily and a subsidised restaurant. We are within commuting distance of Leeds, Manchester and the Yorkshire Dales - and we even have free parking! At our Head Office you will expect to find supplier showcases, charity fundraising and celebrations all year round for the events that mean the most to our colleagues. There's more to our business as it's fast paced and ever changing, as such we've got lots of fresh opportunities for you to play your part in our success. We'd love to meet you! At Morrisons, we're proud to be building a team that reflects the diversity of the communities we serve. We want every colleague to feel respected, supported and able to be themselves at work. Different voices, experiences and ways of thinking help us grow and improve and that's good for our customers too. We're always looking for people from all walks of life to join us and bring their talents to our team. Together, we can build a workplace where everyone has the chance to thrive, make a difference and belong.

Personio's intelligent HR platform helps small and medium-sized organizations unlock the power of people by making complicated, time-consuming tasks simple and efficient. Our team of 1,500 Personios is building user-friendly products that delight our 15,000+ customers and their 1.5 million employees. Ready to make an impact from day one? This role will be Hybrid, based in our London office 2 days a week. Role Responsibilities: What you'll do Design, develop, and deploy robust machine learning and AI systems for a range of products and use cases, including generative AI. Integrate ML and AI models into production systems, ensuring scalability, reliability, and maintainability. Deploy and monitor machine learning models and systems, including CI/CD pipelines, automated testing, monitoring, and model versioning. Leverage cloud platforms (AWS + Snowflake) and ML infrastructure (e.g., SageMaker, feature stores) for scalable deployment. Collaborate with cross functional teams (Product, Customer Experience, and other engineering teams) to deliver AI driven features and insights. Ensure all ML/AI solutions adhere to best practices in data privacy, security, and ethical standards. Contribute to a culture of technical excellence, knowledge sharing, and continuous learning. What you need to succeed University degree in Computer Science, Machine Learning, Data Science, or a related field. 3+ years' experience building and deploying production grade machine learning models. Strong software engineering mindset - ability to write clean, reusable, and scalable code in Python. Experience integrating ML/AI models into production software systems. Solid understanding of MLOps practices, CI/CD pipelines, and automated testing frameworks. Hands on experience with ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). Experience working with backend teams and deploying end to end products What's a plus? Background in data science: comfort with experimentation, A/B testing, and measuring ROI/impact of ML projects (not just accuracy). Experience with NLP or generative AI techniques. Familiarity with cloud based ML infrastructure (AWS, Snowflake, SageMaker, etc.). Why this role? Join a recently created AI team focused exclusively on delivering LLM and ML powered projects with real business impact. Work in a lean, well supported environment focusing on real use cases and improving our users experience. Full ownership of end to end ML delivery: from prototype to production. Exposure to high impact use cases backed by executive sponsorship - high visibility within the organization to build impactful products. Why Personio? Personio is an equal opportunities employer, committed to building an integrative culture where everyone feels welcomed and supported. We embrace uniqueness and understand that our diverse, values driven culture makes us stronger. We are proud to have an inclusive workplace environment that will foster your development no matter your gender, civil status, family status, sexual orientation, religion, age, disability, education level, or race. At Personio, we value in person collaboration while also offering flexibility. This role is office based, with 2 days per week required in your contracted office location. The remaining days can be worked from home or in the office if you prefer. In addition, you'll have 20 Flex Days per year to work remotely from other locations. Aside from our people, culture, and mission, check out some of the other benefits that make Personio a great place to work: Receive a competitive reward package - reevaluated each year - that includes salary, benefits, and pre IPO equity Enjoy 28 days of paid vacation, plus an additional day after 2 and 4 years Make an impact on the environment and society with 1 (fully paid) Impact Day Receive generous family leave, child support, mental health support, and sabbatical opportunities We enjoy gathering for meals, cultural initiatives, and events like local Summer Sessions and year-end celebrations. There's also healthy snacks, drinks, and a weekly catered lunch.

Head of Data - London - Messy Data / Web Crawlers / Data Aggregation High Growth B2B SaaS AI & Machine Learning Platform £90,000 - £100,000 + Significant Equity I am working with a scaling London based technology business where Machine Learning and AI sit at the core of the product. The platform is built around a large-scale dataset created by crawling the web and collecting millions of listings from multiple external sources. That raw data is then structured, matched and analysed to power a suite of SaaS tools used across the market. One of the core technical challenges is that the same entity can appear multiple times across different sources, often with slightly different attributes or descriptions. The platform uses a combination of neural networks and rule based systems to match records and build a reliable dataset over time. They are now hiring a Head of Data to take ownership of their data and AI platform. The Opportunity This is a hands-on leadership role where you will lead a team of 5-6 across Data Science and Data Engineering while remaining technically involved in modelling, machine learning deployment and architectural decisions. The platform runs on AWS and includes large-scale crawlers ingesting significant volumes of external data. However, the architecture has evolved over time and data currently sits across multiple siloed systems. They need someone who understands what good looks like in a modern data platform and can bring structure, coherence and technical direction. You will take ownership of improving the data architecture, strengthening the matching systems and defining a clear data and AI roadmap for the business. Key Areas of Focus Designing and improving a scalable AWS based data platform Rationalising fragmented data across multiple systems Leading the full machine learning lifecycle from ingestion and feature engineering through to deployment Improving neural network and rule based matching systems used to identify the same entities across different sources Embedding robust MLOps and model monitoring Building a coherent data architecture that supports future AI development Leading and developing a team of Data Scientists and Data Engineers The Background That Works Well Relevant experience in environments that deal with messy data from multiple external sources might include: Web crawling or large-scale web data ingestion Marketplace or data aggregation platforms Entity resolution, record linkage or deduplication systems Matching systems or recommendation engines Geospatial or address based data platforms ML systems deployed into production You do not need sector experience, but you should be comfortable working with complex datasets where the same entity appears across multiple sources. What They Are Looking For Strong Data Science background with hands on machine learning experience Experience deploying ML models into production environments Understanding of data engineering concepts and modern cloud data platforms Architectural thinking around data platforms and ML systems Experience working with messy, multi source datasets Leadership experience managing small, high impact teams Someone proactive who can define standards and shape the data roadmap Package Salary: £90,000 - £100,000 Equity: Meaningful equity with real upside (3 year vesting) Location: London - Hybrid working, typically 2-3 days in the office with a pragmatic approach to flexibility This is a high ownership role where you will be shaping the foundations of a data and AI platform inside a scaling technology business. If you enjoy solving complex data problems, building scalable machine learning systems and leading a small but impactful team, I would be keen to speak.

Role Summary We are seeking a highly skilled MLOps Engineer to focus on the deployment, monitoring, and maintenance of machine learning models in production environments. This role is platform-focused and does not involve model development or end-user support. The successful candidate will ensure reliability, scalability, and performance of ML platforms while managing API endpoints and deployment workflows. Key Responsibilities Platform Operations & Monitoring Monitor ML model endpoints and platform health using tools such as Grafana and Domino Data Lab Respond to incidents and alerts; perform code fixes and manage changes via ServiceNow Liaise with Domino Data Lab support to resolve platform-related issues Model Deployment Deploy and maintain ML models in production environments Ensure models integrate seamlessly into automated pipelines Maintain reliability, version control, and governance standards Pipeline Maintenance Collaborate with Data Scientists and Engineers for smooth production handoff Maintain and optimize ML pipelines for stability and scalability Improve performance, resource usage, and automation Automation & Tooling Implement automation for deployment and monitoring Contribute to continuous platform improvements Required Skills & Experience Strong Python programming experience Proven experience deploying and monitoring ML models in production Understanding of model evaluation metrics, data drift, overfitting, and feature importance Experience with AWS services (S3, Redshift, etc.) Hands-on experience with Grafana for monitoring Familiarity with Domino Data Lab (desirable) Strong knowledge of CI/CD, version control, Docker, Kubernetes Excellent troubleshooting and incident management skills Strong stakeholder communication skills

AI Engineer (Generative & Agentic AI) Permanent Location: London (onsite twice a week) Salary: £75,000 - £85,000 Per Annum D.O.E Build intelligent systems that solve real enterprise problems: We're looking for an AI Engineer who wants to do more than just plug into APIs, someone who wants to own the build, shape intelligent systems, and bring advanced GenAI and Agentic AI solutions into real-world production. If you're motivated by tackling messy enterprise problems, not just experimenting with models, this is a role where you'll build systems that genuinely change how organisations operate. Why this role exists: Enterprises are past the experimentation phase. They're asking harder questions: How do we make GenAI stable, scalable, and safe? How do we move from prototypes to production? How do we integrate AI into existing products and workflows? You'll be the engineer who takes these questions and turns them into working, impactful AI systems, not just research pieces or demo-ware. This role is ideal for someone who thrives on building, iterating, and owning AI solutions end-to-end. The Role: As an AI Engineer, you'll be responsible for designing, building, and deploying production-grade AI systems in complex enterprise environments. You will: Build and deploy GenAI, RAG, and Agentic AI systems that solve real business challenges Develop robust pipelines, services, and integrations that turn models into usable products Work across front-end, back-end, and data layers to deliver complete, functioning AI solutions Collaborate with architects, data scientists, and product stakeholders to shape solutions and define delivery paths Take ownership of performance, scalability, and maintainability of AI components Continuously experiment, improve, and bring new ideas forward, without heavy process slowing you down This isn't a research role and it's not "keep the lights on." It's product-driven engineering where you ship real systems into production. Key Responsibilities: AI System Development Build and optimise AI models and pipelines Implement RAG, agentic workflows, and advanced reasoning techniques Deploy LLM-driven features into real products Full-Stack & Platform Engineering Develop APIs, backend services, data flows, and integration layers Contribute to UI/UX when needed as part of end-to-end delivery Ensure clean, scalable engineering across the stack MLOps / LLMOps Own the deployment, monitoring, and iteration of AI systems Use modern tooling to ensure models and pipelines are reliable, observable, and repeatable Collaboration Work closely with cross-functional teams to identify opportunities and translate them into robust engineering solutions Provide technical input into architecture, design discussions, and delivery planning What We're Looking For: Core Experience: Strong Python engineering skills and experience delivering production AI/ML systems Hands-on experience with LLMs, RAG, vector databases, and GenAI frameworks Experience deploying solutions on cloud platforms (AWS, Azure, or GCP) Familiarity with LangChain, LlamaIndex, or agentic frameworks is highly valuable Strong grounding in software engineering best practices (testing, versioning, CI/CD, scalability) Mindset & Behaviours: Seek ownership, not just tasks Enjoy solving real user and business problems, not just model optimisation Thrive in environments where they can experiment and move quickly Communicate clearly with both technical and non-technical stakeholders Want to see their work in production, being used by real people Why Join? Work on impactful AI programmes that go beyond prototypes Build meaningful, high-value systems that people actually use Work with modern GenAI tools, approaches, and delivery models Collaborate with experienced architects, engineers, and innovators Strong investment in engineering excellence, innovation, and personal development If you want to build AI systems that matter, not just experiment with models, this is your next move.

About GBG Enabling safe and rewarding digital lives for genuine people, everywhere We make it our mission to ensure more genuine people have digital access to opportunities, and businesses have access to more genuine people. Our technology draws on diverse and reliable data to create a single point of truth for identity and address verification. With over 30 years of experience behind us our team and technology are focused on enabling safe and rewarding digital lives for everyone. Regardless of age, location or background, genuine people everywhere should be able to digitally prove who they are and where they live. About the team and role CVML Teams At the heart of GBG's Documents and Biometrics portfolio, our team focuses on creating unique and powerful artificial intelligence models. These models are designed to revolutionize KYC verification for our customers. We drive the development of these cutting edge technologies, aiming to provide unparalleled solutions for document verification and digital trust. Collaboration is our cornerstone as we bring together diverse expertise to achieve collective success. Guided by Agile methodology, our daily operations focus on efficiency through automation. Director - Machine Learning The Director of Machine Learning provides strategic, technical, and people leadership for machine learning initiatives across the Documents & Biometrics organization. This role is accountable for defining the long term AI/ML vision and roadmap, translating business and product strategy into impactful ML capabilities, and ensuring the reliable, ethical, and scalable delivery of ML models into production. The Director operates as both a senior technical authority and an organizational leader, driving innovation, mentoring teams, influencing stakeholders, and ensuring that machine learning efforts deliver measurable customer and business value. This role requires deep expertise in machine learning and computer vision, strong leadership capability, and the ability to operate effectively across product, engineering, operations, compliance, and executive leadership functions. What you will do Strategic Leadership & Vision Define, own, and execute the long term AI and Machine Learning strategy for the Documents & Biometrics domain, aligned with company objectives and product roadmaps. Identify opportunities where machine learning can materially improve classification, extraction, fraud detection, image processing, and overall product performance. Serve as a thought leader for AI/ML within the organization, advocating for modern approaches, emerging technologies, and best practices. Technical & Delivery Leadership Provide hands on technical leadership across the full ML lifecycle, including research, model design, experimentation, validation, deployment, and continuous improvement. Raise the bar for technical excellence while fostering an inclusive, high engagement team culture. Oversee the development and productization of ML models addressing real world document and biometric challenges at scale. Establish and evolve robust MLOps practices to ensure reproducibility, reliability, observability, cost effectiveness, and consistent high quality model delivery. Ensure the availability, quality, and scalability of labeled data pipelines necessary to support ongoing model development and accuracy improvement. People & Team Leadership Lead, mentor, and develop a team of senior machine learning engineers and technical leaders, fostering a culture of trust, accountability, collaboration, and continuous learning. Build high performing teams that balance innovation with operational excellence. Set clear expectations, provide regular feedback, and support the professional growth and progression of team members. Builds trust through transparency, technical credibility, and consistent delivery. Cross Functional Collaboration Partner closely with Product Management to define AI/ML roadmaps, prioritize initiatives, and ensure timely and high impact delivery. Collaborate effectively with Engineering, Architecture, Data, Platform, Security, Legal, and Compliance teams to ensure ML systems are scalable, secure, and compliant. Represent Documents & Biometrics in cross company forums related to AI strategy, governance, and innovation. Governance, Ethics & Compliance Ensure that machine learning systems are developed and operated in accordance with applicable AI governance frameworks, regulatory requirements, and ethical best practices. Contribute to company wide AI governance efforts, including AI risk assessment, documentation, explainability, and stakeholder readiness. Promote appropriate AI literacy within the team and ensure responsible design and use of ML technologies. Operational Excellence Manage multiple complex initiatives simultaneously, balancing innovation, delivery commitments, and operational stability. Ensure adherence to industry best practices, architectural standards, and engineering quality bars. Maintain high levels of team morale, engagement, and delivery velocity. Skills we're looking for PhD in AI, Machine Learning, Computer Science, or a related field, or equivalent depth of industry experience. Deep technical expertise in machine learning, computer vision, and deep learning applied to real world, production systems. 10+ years of hands on experience in machine learning and computer vision, with a substantial portion in leadership roles. Significant experience leading and scaling machine learning teams in a product focused environment. Proven track record of delivering ML solutions end to end, from concept through production and ongoing optimization. Strong experience building and operating MLOps pipelines, data workflows, and production ML systems. Demonstrated ability to influence across organizational boundaries and communicate effectively with both technical and non technical stakeholders. Experience operating in highly dynamic, fast moving environments with competing priorities. Experience with regulated environments, AI governance frameworks, or compliance driven ML development would be beneficial Experience delivering ML solutions with measurable customer or business impact at scale To find out more As an equal opportunity employer, we are dedicated to creating a diverse and inclusive workplace where everyone feels valued and empowered. Please inform your GBG Talent Attraction Partner if you require any reasonable adjustments to the interview process. To chat to the Talent Attraction team and find out more about our benefits and why we're a great place to work, drop an email to we'll be in touch. You can also find out more about careers at Unleash your potential and be part of our mission to power safe and rewarding digital lives.

Lead Data Engineer/Head of Data Permanent On behalf of a fantstic cleint we are resourcing for the following role This is a senior, hands-on technical leadership role reporting directly to the CTO. You'll shape and deliver a modern data and AI platform, lead a small team of data and analytics engineers, and embed machine learning, AI agents, and advanced analytics into real customer workflows. The Role You'll own the end-to-end data and AI capability - from platform architecture through to production ML systems - ensuring data and AI are applied thoughtfully, responsibly, and with clear business impact. What You'll Do Design and evolve a secure, scalable data & AI platform with Snowflake at its core Build production-grade data pipelines, models, and data products for analytics and AI use cases Design, train, and deploy ML models, embeddings, and vector stores to enable AI-driven experiences Lead and mentor a small, high-impact team of data and analytics engineers Partner closely with Product, Engineering, and Infrastructure teams Set standards for data quality, governance, security, and performance Act as a trusted technical advisor to the CTO and senior leadership What We're Looking For Essential Expert-level Snowflake experience (modelling, optimisation, advanced features) Strong Python skills across data engineering, ML, and AI development Proven experience delivering production ML systems Hands-on experience with embeddings, vector databases, and LLM-driven systems Deep understanding of modern data engineering practices (ELT, orchestration, versioning) Nice to Have Background in data science or applied ML Experience building AI agents or intelligent automation Familiarity with cloud-native architectures and MLOps

Automated Intelligence SME Clearance Required: SC An opportunity is available for an experienced AI Subject Matter Expert to support the implementation and delivery of Automated Intelligence solutions within secure environments. You will work across technical and business teams to design, develop and deploy AI enabled automation capabilities that integrate into existing enterprise systems. The Role You will support the delivery of AI driven automation initiatives across secure programmes. The position requires strong technical capability combined with stakeholder engagement and risk awareness. Key Responsibilities Design, build and deploy automation solutions integrating AI and machine learning models into existing systems and workflows. Analyse business processes with stakeholders to identify automation opportunities and define clear requirements. Develop automation scripts and build data pipelines covering ingestion, preprocessing and feature engineering. Conduct testing, troubleshooting and performance monitoring to maintain system accuracy and reliability. Collaborate with data scientists, software engineers and IT teams to ensure seamless deployment. Produce clear technical documentation and performance reporting. Support contract discussions, stakeholder engagement and business risk considerations where required. Technical Skills Required Proficiency in programming languages such as Python, Java, C# or R. Experience with machine learning frameworks including TensorFlow, PyTorch or Scikit-learn. Familiarity with cloud platforms such as AWS, Azure or Google Cloud and associated MLOps practices. Experience with automation and orchestration tooling such as UiPath, Airflow or Kubeflow. Experience and Capability Strong experience delivering AI or automation solutions within enterprise environments. Ability to work with cross functional teams and translate technical solutions into business value. Experience operating within controlled or regulated environments. Strong written and verbal communication skills. Experience supporting stakeholder engagement and business risk management. This role suits a technically credible AI professional who can design and implement automation solutions while engaging effectively across secure and regulated programmes. To apply, please send your CV by pressing the apply button

We're hiring an experienced AI Platform Engineer to design, build and operate a production-grade Generative AI platform powering next-generation intelligent products. This is a hands-on engineering role focused on taking AI solutions from prototype to scalable, reliable services used in real-world environments. You'll sit at the intersection of DevOps, cloud infrastructure and applied AI owning the full lifecycle of Retrieval-Augmented Generation (RAG) and LLM-powered systems across modern cloud architecture. This role is about engineering, not research. You will architect and run the infrastructure that enables AI to perform securely, reliably and at scale ensuring performance, cost control and operational maturity as adoption grows. You'll work closely with AI engineers, security teams, and product stakeholders to transform experimental models into hardened, production-ready services while shaping a reusable AI platform capable of supporting multiple products. What You'll Be Doing Design and optimise scalable RAG pipelines and vector search systems Orchestrate multi-model AI services with a focus on latency, resilience and performance Productionise GenAI workflows and ensure they operate reliably under real usage Build and run AI services across AWS and Databricks Develop ingestion, embedding and retrieval pipelines Deploy containerised workloads via Kubernetes and Helm Implement Infrastructure-as-Code using Terraform Introduce end-to-end monitoring, tracing and alerting for AI workloads Improve inference and retrieval performance while reducing operational cost Establish fault-tolerant, scalable infrastructure patterns Embed security, evaluation and governance into the AI lifecycle Build CI/CD pipelines and automation to support continuous model deployment Create reusable platform components to accelerate future AI initiatives Strong experience in: Cloud infrastructure engineering (AWS-focused environments) Kubernetes, containerisation, and distributed systems Terraform / Infrastructure-as-Code CI/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data / AI workflow orchestration in Databricks or similar ecosystems Why Join? Work on real-world AI systems operating at scale Own platform design decisions and influence long-term architecture Blend modern DevOps practices with cutting-edge Generative AI use cases Be part of a growing, innovation-driven engineering environment Opportunity to define how AI is operationalised across multiple products If you're excited by building the infrastructure that makes AI usable, scalable and reliable in production, we'd love to hear from you. 49914MS INDLON Portfolio Payroll Ltd is acting as an Employment Agency in relation to this vacancy.