25 days ago
Manchester, United Kingdom +3 moreStaff+
Responsibilities
- Design and deliver end-to-end AI/ML systems from data preparation and model development through deployment, feature stores, model management, and monitoring.
- Architect and implement generative AI and agentic AI solutions, including RAG pipelines, agentic workflows, MCP integrations, and LLM orchestration.
- Translate AI use cases into cloud-native data and AI architectures using Azure, GCP, AWS, and/or Databricks.
- Lead multidisciplinary teams delivering complex client requirements and collaborate with technical and non-technical stakeholders.
- Embed safety, evaluation, assurance, explainability, and responsible AI mechanisms across the AI lifecycle.
- Build client-ready demos and proofs of value, support proposals and technical deep-dives, and showcase delivery patterns.
- Develop reusable assets, frameworks, internal accelerators, thought leadership, and best practices for AI engineering.
Requirements
- Experience in a major consulting firm or industry role with a consulting mindset and success in matrixed organizations.
- Experience working with client sponsors and collaboratively designing requirements and solutions.
- Experience designing and implementing MLOps strategies and frameworks and delivering AI/ML solutions from concept to production at scale.
- Deep understanding of generative AI and agentic AI, including RAG pipelines, embeddings, evaluation harnesses, and orchestration frameworks.
- Experience designing cloud-native data and AI architectures across Azure, GCP, AWS, and/or Databricks.
- Experience deploying and scaling AI solutions on at least one major cloud platform.
- Experience building and automating AI/ML pipelines with tools such as MLflow, Kubeflow, Azure ML, Vertex Pipelines, Airflow, or Google ADK.
- Hands-on experience with generative and agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, Autogen, or Google ADK.
- Ability to design RAG pipelines and agentic workflows and integrate with LLM APIs including OpenAI, Anthropic, or Hugging Face.
- Proficiency with CI/CD and containerization technologies including GitHub Actions, Azure DevOps, Docker, and Kubernetes.
- Familiarity with AI evaluation, prompt evaluation, A/B testing, quality assessment frameworks, lakehouse architectures, vector databases, relational and NoSQL stores, API gateways, event streaming, and integration patterns.
- Must have resided in the UK for the last five years to apply.
Benefits
- Hybrid working and flexible working arrangements are available to UK employees.
- Employees have an office base location but must be fully flexible regarding assignment locations, including periods away from home at short notice.
- Flexible benefits options are included in the remuneration package.
- Variable compensation depends on grade and company and personal performance.
- Employee wellbeing support includes Mental Health Champions and wellbeing apps such as Thrive and Peppy.
- The company promotes diversity and inclusion, work-life balance, and social and environmental impact initiatives.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.