1 day ago
Responsibilities
- Collaborate with data engineers, data scientists, and business stakeholders to understand data and business problems.
- Design, implement, and deploy end-to-end generative AI, agentic AI, and machine learning solutions.
- Build and deploy GenAI applications using agent frameworks such as Langgraph, Autogen, and Crew AI.
- Implement advanced RAG solutions using multiple large language models and vector databases.
- Process and ingest unstructured data from PDFs, HTML, images, and audio-to-text sources.
- Develop web user interfaces, machine learning models and pipelines, GenAI solutions, and agentic AI solutions.
- Build RESTful APIs and apply system architecture and coding best practices.
- Evaluate and fine-tune LLMs, including local deployment of open-source models.
- Work with cloud AI stacks and services across AWS, GCP, and Azure.
- Apply data gathering, data quality, applied statistics, and data visualization practices.
Requirements
- Bachelor's degree in computer science, engineering, mathematics, statistics, or a related field.
- Strong hands-on experience with GenAI, agentic AI, data science, and machine learning.
- Proficiency in Python and common machine learning libraries including TensorFlow, PyTorch, and Scikit-learn.
- Experience with agentic AI frameworks such as Autogen, Crew AI, Semantic Kernel, and Langgraph.
- Experience with LLM fine-tuning, open-source model deployment, advanced RAG, and multiple large language models.
- Hands-on experience with vector databases such as FAISS, Pinecone, Weaviate, or Azure AI Search.
- Proficiency with SQL and NoSQL databases including PostgreSQL, MongoDB, CosmosDB, and DynamoDB.
- Experience with CI/CD pipelines and DevOps tools including Jenkins, GitHub Actions, or Terraform.
- Proficiency building APIs with FastAPI, Flask, or Django.
- Knowledge of model evaluation tools including DeepEval, FMeval, RAGAS, and Bedrock model evaluation.
- Experience with computer vision, time series data, text analysis, Tableau, SQL, and Hive.
- Strong applied statistics skills, including distributions, statistical testing, and regression.
Tech Stack
Amazon DynamoDBApache HiveAWSAzureDjangoFastAPIFlaskGitHub ActionsGoogle Cloud PlatformHTMLJenkinsMongoDBPostgreSQLPythonPyTorchscikit-learnSQLTensorFlowTerraform
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About Capgemini
Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion. Make it real | www.capgemini.com