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Capgemini

Global consulting, technology services, outsourcing

AI Engineering Consultant / Senior Consultant

Applied Machine LearningUpdated on Nov 14
Full-time

About the Job

Requirements

  • Experience at a major consulting firm, or industry experience with a consulting mindset and a proven ability to succeed in a matrixed organization and enlist peer support for selling and delivering solutions.
  • Experience working with technical and non-technical client sponsors to collaboratively design requirements and build solutions.
  • Experience designing and implementing MLOps strategies and frameworks, with a proven track record of delivering AI and machine-learning solutions at scale from concept to production.
  • Deep understanding of generative AI and agentic AI, including retrieval-augmented generation (RAG) pipelines, embeddings, evaluation harnesses, and orchestration frameworks.
  • Experience designing cloud-native data and AI architectures across Azure, Google Cloud Platform, Amazon Web Services, and/or Databricks.
  • Ability to demonstrate how scaling AI can unlock business value and impact.
  • Experience with at least one major cloud platform, such as Azure (Foundry, AI Studio, OpenAI, AKS), Google Cloud Platform (Vertex AI, Cloud Run), or Amazon Web Services (Bedrock, SageMaker).
  • Experience building and automating AI and machine-learning pipelines using tools such as MLflow, Kubeflow, Azure Machine Learning, Vertex Pipelines, Airflow, or Google ADK.
  • Hands-on experience with generative and agentic AI frameworks such as LangChain, LlamaIndex, CrewAI, AutoGen, Google ADK, or similar.
  • Ability to design and implement RAG pipelines, agentic workflows, Model Context Protocol (MCP), and integrations with large language model APIs such as OpenAI, Anthropic, or Hugging Face.
  • Proficiency in continuous integration and continuous delivery (CI/CD) and containerization, including GitHub Actions, Azure DevOps, Docker, and Kubernetes.
  • Must have resided in the United Kingdom for the last five years to apply.

Responsibilities

  • Assess and implement robust MLOps frameworks, governance, and industry-standard best practices.
  • Design and deliver end-to-end AI and machine-learning systems, from data preparation and model development through model deployment, feature stores, model management, and monitoring.
  • Deliver solutions using generative AI and agentic frameworks, such as ADK, LangGraph, Microsoft Agent Framework, and LlamaIndex.
  • Translate AI use-case requirements into data and AI architectures using suitable cloud services across hyperscalers.
  • Architect and implement generative AI solutions, including RAG pipelines, agentic workflows, and orchestration of large language models across Azure, Google Cloud Platform, or Amazon Web Services.
  • Embed safety, evaluation, and assurance mechanisms across the AI lifecycle to ensure solutions are ethical, explainable, and responsible.
  • Translate business and functional requirements into technical blueprints and guide multidisciplinary teams in executing them.
  • Collaborate with product managers, data scientists, and business stakeholders to ensure AI solutions deliver business value and impact.
  • Build client-ready demonstrations and proofs of value, support proposals and technical deep dives, and showcase delivery patterns.
  • Build reusable assets and frameworks that accelerate delivery across accounts, shape frameworks for Capgemini's Data & AI Innovation team, and contribute to internal communities and best practices.
  • Contribute to thought leadership, blog posts, or internal accelerator development in emerging AI engineering topics such as agentic AI, LLMOps, or evaluation frameworks.

Desired Qualifications

  • Familiarity with evaluating AI system performance, including prompt evaluation, A/B testing, and quality-assessment frameworks.
  • Understanding of modern data patterns, including lakehouse architectures, vector databases, and relational and NoSQL data stores.
  • Familiarity with API gateways, event streaming, and general integration patterns.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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