AI Engineer 💛

We are seeking a skilled and innovative AI Engineer with Full Stack Development expertise who has experience working with Generative AI (GenAI) models, such as Large Language Models (LLMs), and implementing these solutions into web applications. This role combines the responsibilities of a full-stack developer with advanced knowledge of machine learning models, APIs, and cloud infrastructure, focusing on integrating state-of-the-art AI capabilities into user-friendly and efficient web-based applications.

Key Responsibilities:

Model Integration & API Development:

• Integrate LLMs and other GenAI models into web applications through efficient API design and implementation.
• Build and optimize API endpoints to allow seamless, real-time interaction between front-end applications and back-end AI models.
• Design and develop secure, scalable, and high-performing microservices for AI model deployment.

Front-End Development:

• Design and develop responsive and intuitive front-end applications using React.js to enhance the user experience of AI-powered applications.
• Implement front-end components to visualize, interpret, and manage AI model outputs effectively.

Back-End Development & AI Pipelines:

• Develop robust back-end systems in Python to support the deployment, scalability, and maintenance of GenAI models.
• Build and maintain data pipelines, including preprocessing data and post-processing AI model outputs for consumption by applications.
• Implement best practices for handling sensitive data and maintaining model performance.

Infrastructure & Deployment:

• Use Kubernetes and Docker for containerization and orchestration to ensure scalable deployment and management of AI applications.
• Implement continuous integration and continuous deployment (CI/CD) pipelines for automated testing and deployment of code changes.
• Maintain a scalable and secure cloud infrastructure, leveraging platforms such as Google Cloud Platform, or Azure for model training, storage, and deployment.

LLM and GenAI Ecosystem Expertise:

• Utilize vector databases (e.g., Pinecone, Weaviate, or Faiss) to manage and retrieve embeddings for efficient similarity search and recommendation systems.
• Work with frameworks for model development and deployment, including Hugging Face Transformers, LangChain, and OpenAI.
• Optimize and fine-tune LLMs to improve performance based on application needs.

Required Qualifications:

• Min Bachelor's degree in Computer Science, Engineering, or a related field.
• 3+ years of experience as a full-stack developer, ideally with a focus on AI model integration.
• Proficiency in Python for backend development and React.js for frontend development.
• Strong knowledge of GenAI models and LLMs, including experience with model selection, tuning, and embedding strategies.
• Experience with API development and integration to facilitate communication between front-end applications and AI models.
• Working knowledge of containerization technologies like Docker and container orchestration with Kubernetes.
• Familiarity with cloud platforms (AWS, GCP, or Azure) for AI model deployment and scalability.
• Proficiency in vector databases and their integration with LLM models for enhanced application functionality.
• Familiarity with database management (SQL, NoSQL) and caching solutions (e.g., Redis).
• Experience in CI/CD pipelines, code versioning (Git), and DevOps practices.
• Excellent knowledge of English AND Polish.

Preferred Qualifications:

• Knowledge of streaming architectures for real-time data processing and ingestion (e.g., Apache Kafka).
• Familiarity with serverless architectures (e.g., AWS Lambda) for scalable deployment of AI features.
• Prior experience in ML frameworks like TensorFlow, PyTorch, or ONNX.
• Understanding of data privacy and security best practices in AI applications.

Soft Skills:

• Strong problem-solving skills and ability to work independently and as part of a team.
• Excellent communication skills to translate technical requirements into actionable development tasks.
• Proactive approach to staying updated with emerging AI technologies and frameworks.

This is a unique opportunity to work on cutting-edge AI applications that leverage the latest advancements in Generative AI and Large Language Models, impacting the future of intelligent software development.