Full Stack Developer - Gen AI

• Amsterdam, Noord-Holland

• Vast

• Voltijds

• 14 uren geleden

As a Full Stack Developer - Gen AI, you will:

• Design, develop, and implement Generative AI solutions aligned with business use cases.

• Build LLM-powered applications using techniques such as prompt engineering, embeddings, and Retrieval Augmented Generation (RAG).

• Develop AI Proof of Concepts (POCs) and MVPs and scale them into production-ready applications.

• Build backend services and APIs using Python frameworks such as FastAPI, Flask, or Django.

• Develop and integrate frontend components for AI-enabled web applications using modern UI frameworks.

• Deploy and manage AI solutions on Azure Cloud, including Azure OpenAI and Azure Machine Learning services.

• Fine-tune, evaluate, and optimize large language models (LLMs) for performance, cost efficiency, and accuracy.

• Implement logging, monitoring, security, and performance optimization for AI applications.

• Collaborate with cross-functional teams including product, engineering, and stakeholders to deliver scalable AI solutions.

• 4-6 years of overall experience in software development with strong exposure to AI / Generative AI development.

• Strong proficiency in Python programming.

• Hands-on experience building Generative AI and LLM-based applications.

• Experience with prompt engineering, embeddings, and RAG pipelines.

• Full stack development experience including backend APIs and frontend integration.

• Experience with Azure Cloud services, particularly Azure OpenAI and Azure ML.

• Experience working with REST APIs and SQL databases (MySQL preferred).

• Strong knowledge of data processing libraries such as Pandas and NumPy.

You should possess the ability to:

• Develop scalable AI-powered applications for enterprise environments.

• Translate business problems into AI-driven technical solutions.

• Integrate LLM capabilities into web applications and APIs.

• Optimize models and pipelines for performance, cost, and accuracy.

• Work effectively in agile and collaborative environments.

• Troubleshoot and improve AI application performance and reliability.