1,051 to 1,075 of 2,054 Use Case Jobs in England

engineering teams and our delivery partner, and you will play a central role in proving the platform through priority business use cases.As a Product Owner, you will be responsible for translating API strategy into deliverable outcomes, ensuring teams are focused on the highest-value priorities and delivering capabilities … feedback, usage data and stakeholder insight to improve products and services.Promote API reuse and adoption across internal and external consumers.Define success measures and use data and insight to assess performance and value delivered.Support release planning, implementation and continuous improvement activities.Help identify opportunities to use AI, automation ...

across the ICB to drive efficiency, quality and automation. Developing orchestration pipelines, prompt engineering frameworks, APIs and workflow automation supporting corporate and operational use cases. Implementing safeguards including monitoring, observability, evaluation, audit logging and human-in-the-loop controls. Working with operational leaders across the ICB to identify … responsible staff culture. At our Organisation, our selection process ensures we recruit candidates with the right skills and values. We monitor AI use in applications and remain alert to misuse that misrepresents abilities. You must declare any AI use when submitting your application. Job description ...

will define and own the platform strategy, governance model, operating model, and engineering standards, ensuring that the platform enables scalable data products, AI use cases, and self-service analytics. Beyond platform stability and delivery, you will drive innovation in the agentic AI space, enabling new ways of working … compliance (data, AI, access, regulatory) Cost management (FinOps for data and AI platforms) Platform standards, adoption and best practices Enabling business-driven use cases at scale Responsibilities Key duties and responsibilities Under the responsibility of the Head of Data Platform , your mission will be to: Define and execute ...

programme, not just in theory ML and AI platform work: feature stores, MLflow, model serving, and the data foundations behind RAG or agentic use cases Regulated-sector exposure — financial services, healthcare, public sector — and the assurance that comes with it How you work Opinionated but not dogmatic: recommends … says so when a client's preferred tool is the wrong one Comfortable being the only data person in the room and building the case from scratch Writes clearly — decision records, options papers and diagrams a client executive can act on Commercially aware: understands utilisation, margin ...

Work directly with client stakeholders to understand business requirements and translate them into scalable data and AI solutions. Support AI and Generative AI use cases using Oracle AI Services, OCI Generative AI, Vector Search and Oracle Database 23ai (or above) capabilities. Guide development teams and provide hands … managing discrete client engagement Ability to build and maintain relationships with clients. Multiple lifecycle implementations of Oracle AI solutions, including the following phases: business case, requirements gathering, fit/gap analysis, Cloud architecture, design documentation, and deployment. Set Yourself Apart: Confidence in presenting challenging points of view to client ...

services to deliver accurate, timely customer migrations Key Responsibilities: Apply classification, regression, ranking, forecasting, clustering, and anomaly detection to enterprise AI and agentic use cases. Develop and evaluate intent classification, semantic matching, agent/skill/tool ranking, and model-routing techniques; compare learned approaches with rules, embeddings … based baselines. Use statistical modeling to estimate execution latency, token demand, inference costs, workload trends, and resource requirements. Apply clustering and anomaly detection to identify recurring intents, capability gaps, unusual agent behavior, and execution regressions. Conduct exploratory analysis, dataset preparation, feature engineering, hypothesis testing, and reproducible experiments. Foundation ...

solutions Manage customer engagements from discovery and requirements gathering through technical onboarding, training, feedback collection and completion Conduct workflow assessments to identify customer use cases, business requirements and opportunities for artificial intelligence-enabled improvements Support customers with solution configuration, access, entitlements, application programming interface integrations and technical setup … documentation Provide best-practice and consultative guidance to support stable deployments and effective solution adoption Partner with prospective and existing customers to validate use cases and support strategic commercial opportunities Collaborate with client technical teams and internal subject-matter experts to investigate and resolve product, data, access ...

clients, buying centres, business challenges and AI opportunity areas where NTT DATA can create differentiated value.Develop a focused portfolio of Banking AI propositions, use cases and client narratives spanning Generative AI, agentic AI, machine learning, automation and intelligent decisioning.Translate developments in AI into relevant Banking propositions across areas … strategy sessions, executive workshops, ideation sessions and opportunity prioritisation exercises.Help Banking clients move from experimentation toward enterprise-scale AI adoption by connecting use cases to business outcomes, operating model change, data readiness, governance and responsible AI.Develop strong relationships with senior stakeholders across business, technology, data, operations, risk ...

What You Will Do Design and build agentic AI applications and multi-agent workflows, along with the frameworks that run them, for enterprise use cases Build RAG pipelines and integrate LLM APIs, vector databases, and MCP (Model Context Protocol) tooling Process unstructured data into condensed, structured knowledge, including … Work closely with platform engineering throughout deployment - hosting, scaling, and MLOps/LLMOps - without owning that infrastructure yourself Define AI governance and responsible-use guardrails: data privacy boundaries, LLM governance, and policy enforcement (OPA/Rego) Instrument AI applications for observability (OpenTelemetry, Prometheus) so behaviour and cost stay ...

Partner with CFO organizations to improve operational efficiency, effectiveness, and business insights. AI & Generative AI Enablement Identify, assess, and prioritize AI and GenAI use cases across finance processes. Design and implement AI-powered solutions for financial reporting, forecasting, reconciliations, variance analysis, close management, and decision support. Leverage … from each other every day, sharing knowledge, and always pushing yourself to do better, you’ll build the skills you want. You’ll use your skills to help our clients leverage technology to innovate and grow their business. So, it might not always be easy, but making ...

evaluation criteria, running proofs of concept with engineering, documenting trade-offs, and driving build-vs-buy decisions Source, qualify, and prioritize Knowledge Graph use cases across product sub-teams, maintaining a transparent backlog with clear value hypotheses, success metrics, and prioritization rationale Translate ambiguous business problems into precise … consuming product teams — communicating progress, trade-offs, and risks clearly to both technical and non-technical audiences Define onboarding paths for new use cases, drive platform adoption, and feed learnings back into the roadmap to support continuous improvement About the Team Our Risk Insights team is responsible ...

lifecycle management Develop innovative machine learning solutions, including generative AI and multi‐agent approaches, and define evaluation, safety, and monitoring strategies for production use Own production deployment patterns including containerization, continuous integration and delivery, automated testing, model and prompt registries, model and version governance, monitoring and alerting … influence roadmaps, align on requirements, and deliver data‐led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews ...

pipeline development. Experience in building scalable and resilient data platforms in the public cloud. Data modelling and wrangling expertise to support advanced analytical use cases and ML, AI opportunities. Experience with containerisation technologies ( Docker, Kubernetes ) for scalable data solutions. Experience with vector databases and graph databases (e.g., Pinecone … data integrations acrossETL and streaming services ( Glue, MSK, Kinesis, Kafka ) Familiarity with AI developer tools like Cursor and GitHub Copilot and desire to use them to 10x your throughput. Collaborative approach and excellent communication skills. Strong problem-solving abilities and creative thinking, with critical thinking credentials to solve ...

internal knowledge and ownership. This is a rare opportunity to join a new leadership organization and to help set how the Teva will use data, analytics and AI to modernize decision making, automate critical processes, and accelerate innovation across core functions and value chains. The Role … data platforms, and enterprise AI enablement. How You'll Spend Your Day Own end-to-end solution architecture for data, analytics, and AI use cases, with accountability for design quality, security, scalability, supportability, and cost. Translate business needs into practical technical designs, target architectures, integration patterns, and delivery ...

Write advanced SQL for data transformation, reconciliation, profiling and analysis across OLTP and analytical data platforms. Design data models for operational and analytical use cases, including dimensional modelling, slowly changing dimensions, lakehouse and data-lake patterns. Work with platforms such as Snowflake and relational databases including … testable, supportable and delivered with clear documentation. Data issues are identified early, investigated rigorously and resolved through sustainable engineering solutions. Audit stakeholders can use consistent, trusted data more efficiently. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders ...

will keep the delivery lead and client stakeholders informed about progress, risks and trade-offs. You will work across customer-facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval-augmented generation solutions and agentic workflows. This is a technical role. You will be expected … agentic workflows. You have written the code yourself on at least some of these, and you understand how prompting, context management, retrieval, tool use, orchestration, evaluation and guardrails work in practice. AI and data science foundations. Good understanding of machine learning and data science alongside generative AI. ...

organisation who makes a huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering … also had experience in some of these, but if not we'll help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation ...

organisation who makes a huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering … also had experience in some of these, but if not we’ll help you with them: Experience with advanced LLM techniques: agents, tool use, and agentic workflows Experience with vector databases (Pinecone, Weaviate, pgvector) for RAG applications Experience with feature stores (Feast, AWS Feature Store) Experience with containerisation ...

design the solutions to deliver to the requirements coming from different business lines and operational departments that have data provision, reporting, and analytics use cases. This is to keep us aligned with the longer term agreed strategies at a business, data, and technical level. The role … technical strategy and drive its consist application where possible. Engage with other departments across IT and the business, including Data Office, to understand use cases for setting the technical strategy and developing solution designs. Communicate and explain solutions to technical delivery teams. Escalate any issues to Lead Data ...

will keep the delivery lead and client stakeholders informed about progress, risks and trade‐offs. You will work across customer-facing AI use cases including personalisation, customer decisioning, customer service agents, retrieval‐augmented generation solutions and agentic workflows. This is a technical role. You will be expected … agentic workflows. You have written the code yourself on at least some of these, and you understand how prompting, context management, retrieval, tool use, orchestration, evaluation and guardrails work in practice. AI and data science foundations. Good understanding of machine learning and data science alongside generative AI. ...

with Client Platform strategy and the target operating model.Partner with the Wealth and Institutional Product Owners to understand where workflows, data needs, analytical use cases, and operating requirements are shared and where they materially differ. Translate those needs into scalable horizontal data and analytics capabilities, balancing standardization, reusability … have clear, refined work, timely product decisions, and early visibility into risks and dependencies, resulting in predictable delivery and limited avoidable rework.Workflow improvements use process change, technology, data, automation, and AI where they provide meaningful value and can be implemented and governed responsibly.QUALIFICATIONS Experience10+ years of experience ...

efficient and reliable. AI is central to how we work at Zego, and that extends to engineering. You'll be encouraged to use AI tools to move faster, automate the routine, and focus your time on the problems that matter most, while staying thoughtful about where … streaming systems within our existing architecture. Ensure data is modelled and structured to meet the needs of analytics, data science, and operational use cases. Contribute to improvements in our data systems and tooling. Collaboration & Delivery Work with teams across the business to understand requirements and turn them into ...

firm. The goal is trusted, reusable data products that support investment decisions, client reporting, regulatory submissions and a growing range of AI use cases. As Head of Data Engineering, you will report to the Director of Data, AI & Analytics and lead a growing data engineering team across London … general engineering management role. We want a practitioner who has built modern data platforms hands-on. You should know how to use modern data technologies to design scalable solutions that deliver real business outcomes. What You will Do Shape a modern data platform. Own the design, build ...

Working with our most strategic global accounts, you will diagnose their strategy and key operational challenges to discover and build tailored, domain-specific use cases. You will architect and prototype state-of-the-art AI and technical solutions on the Celonis platform, demonstrate their business impact … suite executives and seamlessly connect complex, systemic bottlenecks to strategic AI solutions.Agentic AI Systems: Advanced architectural mastery of LLM orchestration, tool use/function calling, RAG, agents, prompt engineering, and agentic patterns for enterprise workflows.Math & Operations Research: Practical, expert-level application of linear/nonlinear optimization, rigorous statistical ...

join the AI Platform team. This team builds and maintains Flo’s shared platform for artificial intelligence, enabling every product team to use AI safely, efficiently, and at scale. If you’re passionate about cutting‐edge generative AI technologies and driven by building robust ML infrastructure that delivers … central enabler of machine learning and AI initiatives across the organisation. Its mission is to reduce operational overhead and maximise ROI from ML use cases. The team builds and maintains critical infrastructure including LLM evaluation frameworks (AI Judges), model deployment pipelines, fine‐tuning infrastructure, user profiles store, experiment ...