Fullstack Gen AI Developer

Capgemini is a global leader partnering with companies to transform and manage their business by harnessing the power of technology. The group has over 360,000 team members worldwide and boasts 55 years of heritage and deep industry expertise. Capgemini Invent focuses on inventive transformation consulting, blending strategic, creative, and scientific capabilities to deliver cutting-edge solutions informed by science and data and powered by technology.

• Passion for Generative AI and fullstack development with hands-on experience delivering AI-powered web applications
• 2+ years of software development experience in both frontend and backend environments
• Strong programming skills in Python, JavaScript, TypeScript and experience with frameworks such as FastAPI, Flask, Node.js, React, and Next.js
• Working knowledge of large language models (LLMs), prompt engineering, fine-tuning, and retrieval-augmented generation (RAG)
• Experience connecting to Generative AI APIs and managing vector databases like FAISS, Pinecone, or Weaviate
• Familiarity with cloud platforms including AWS, Azure, GCP and CI/CD pipelines for deploying AI-driven applications
• Understanding of data pipelines, embeddings, and model-serving infrastructure
• Strong communication skills in English; German or Polish is a plus

Nice to have:

• Experience with LangChain, LangGraph, OpenAI Function Calling, or custom agent frameworks
• Familiarity with Vercel AI SDK, Next.js Server Actions, or other GenAI-focused web stacks
• Background in UX for AI applications, multimodal systems, or real-time AI interfaces like chat or co-creation tools
• Experience building end-to-end prototypes or AI SaaS products from concept to production

• Design, build, and deploy fullstack Generative AI applications integrating advanced LLMs, image, and multimodal models
• Develop and maintain frontend interfaces with React, Next.js, and backend systems using Python, Node.js, FastAPI, and Flask
• Implement AI-driven workflows including prompt orchestration, retrieval-augmented generation (RAG) pipelines, and real-time model interactions
• Integrate foundation models and APIs such as OpenAI, Anthropic, Hugging Face, and Stability into backend services and user experiences
• Collaborate with data scientists and product teams to translate business requirements into AI-enabled digital experiences
• Ensure system scalability, performance, and security leveraging cloud infrastructure and MLOps practices
• Stay updated with Generative AI innovations, experimenting with new models, frameworks, and architectures