AI Engineer

Job Description

As a Gen AI Engineer at StatusNeo, your primary role is to develop, optimize, and deploy AI models and solutions with a specific focus on Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG) models, and Large Language Models (LLMs). You will work closely with cross-functional teams to design and implement scalable AI solutions on various cloud platforms.

Key Responsibilities:
- Design, train, and fine-tune generative AI models, LLMs, and RAG models to address specific business use cases.
- Develop, test, and optimize prompts to enhance the performance and accuracy of AI models in generating desired outputs.
- Deploy and manage AI models on cloud platforms (e.g., AWS, Azure, GCP) ensuring scalability, security, and cost-efficiency.
- Collaborate with data scientists and engineers to ensure high-quality data ingestion, preprocessing, and feature engineering.
- Continuously monitor and evaluate model performance, making adjustments to improve accuracy and efficiency.
- Stay updated with the latest advancements in AI, LLMs, and cloud technologies, and incorporate new techniques and tools into the development process.
- Work closely with product managers, software engineers, and other stakeholders to integrate AI solutions into products and services.
- Maintain comprehensive documentation of models, algorithms, and development processes to ensure transparency and reproducibility.

Qualifications:
- Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or a related field.
- Proven experience in developing and deploying AI models, particularly in Generative AI, LLMs, and RAG models. 
- Hands-on experience with cloud platforms like AWS, Azure, or GCP for AI/ML workloads.
- Strong background in Prompt Engineering and AI model optimization techniques.
- Proficiency in programming languages such as Python, TensorFlow, PyTorch, or similar frameworks.
- Experience with NLP, machine learning algorithms, and data preprocessing.
- Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes) is a plus.
- Familiarity with MLOps practices and tools for continuous integration and deployment.
- Strong problem-solving skills, ability to work in a fast-paced environment, excellent communication, and teamwork abilities.

(Note: No additional details about the company were provided in the job description),