<p>We are seeking a skilled and innovative AI Engineer 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. </p><h3>Key Activities: </h3><h3>Model Integration &amp; API Development: </h3><ul><li>Integrate LLMs and other GenAI models into web applications through efficient API design and implementation. </li><li>Build and optimize API endpoints to allow seamless, real-time interaction between front-end applications and back-end AI models. </li><li>Design and develop secure, scalable, and high-performing microservices for AI model deployment. </li></ul><h3>Back-End Development &amp; AI Pipelines: </h3><ul><li>Develop robust back-end systems in Python to support the deployment, scalability, and maintenance of GenAI models. </li><li>Build and maintain data pipelines, including preprocessing data and post-processing AI model outputs for consumption by applications. </li><li>Implement best practices for handling sensitive data and maintaining model performance. </li></ul><h3>Infrastructure &amp; Deployment: </h3><ul><li>Use Kubernetes and Docker for containerization and orchestration to ensure scalable deployment and management of AI applications. </li><li>Implement continuous integration and continuous deployment (CI/CD) pipelines for automated testing and deployment of code changes. </li><li>Maintain a scalable and secure cloud infrastructure, leveraging platforms such as Google Cloud Platform, or Azure for model training, storage, and deployment. </li></ul><h3>LLM and GenAI Ecosystem Expertise: </h3><ul><li>Utilize vector databases (e.g., Pinecone, Weaviate, or Faiss) to manage and retrieve embeddings for efficient similarity search and recommendation systems. </li><li>Work with frameworks for model development and deployment, including Hugging Face Transformers, LangChain, and OpenAI. </li><li>Optimize and fine-tune LLMs to improve performance based on application needs. </li></ul><ul><li>Min Bachelor's degree in Computer Science, Engineering, or a related field. </li><li>7+ years of experience as a full-stack developer, ideally with a focus on AI model integration. </li><li>Proficiency in Python</li><li>Strong knowledge of GenAI models and LLMs, including experience with model selection, tuning, and embedding strategies. </li><li>Experience with API development and integration to facilitate communication between front-end applications and AI models. </li><li>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. </li><li>Proficient in vector