Fullstack Gen AI Developer

Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group has over 360,000 team members globally in more than 50 countries. Capgemini Invent operates as inventive transformation consultants blending strategic, creative, and scientific capabilities to deliver cutting-edge solutions.

• Passion for Generative AI and fullstack development with hands-on experience delivering AI-powered web applications.
• 2+ years of software development experience covering both frontend and backend.
• Strong programming skills in Python, JavaScript, and TypeScript with experience in frameworks such as FastAPI, Flask, Node.js, React, Next.js.
• Working knowledge of LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Experience connecting to GenAI APIs and managing vector databases like FAISS, Pinecone, Weaviate.
• Familiarity with cloud platforms (AWS, Azure, GCP) and CI/CD pipelines for AI-driven applications.
• Understanding of data pipelines, embeddings, and model-serving infrastructure.
• Strong communication skills in English; knowledge of 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.
• 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 (React, Next.js) and backend systems (Python, Node.js) supporting GenAI features.
• Implement AI-driven workflows including prompt orchestration, RAG pipelines, and real-time model interactions.
• Integrate foundation models and APIs (such as OpenAI, Anthropic, Hugging Face, Stability) into backend services and user experiences.
• Collaborate with data scientists and product teams to translate business requirements into AI-enabled digital experiences.
• Ensure scalability, performance, and security leveraging cloud infrastructure and MLOps best practices.
• Stay updated with the latest GenAI innovations, experimenting with new models, frameworks, and architectures.