Generative AI Engineer - LLM / RAG Models

Our Client :

Our Client is a global technology consulting and software engineering firm founded in 2020. Headquartered in Gurugram, India, with a U.S. office in Dallas, they employ around 300750 professionalsAs a Gen AI Engineer you will be responsible for developing, optimizing, and deploying AI models and solutions with a focus on Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG) models, and Large Language Models Role :

You will collaborate closely with cross-functional teams to design and implement scalable AI solutions on various cloud Responsibilities :

• AI Model Development : Design, train, and fine-tune generative AI models, LLMs, and RAG models to address specific business use cases.
• Prompt Engineering : Develop, test, and optimize prompts to enhance the performance and accuracy of AI models in generating desired outputs.
• Cloud Expertise : Deploy and manage AI models on cloud platforms (e.g., AWS, Azure, GCP) ensuring scalability, security, and cost-efficiency.
• Data Management : Collaborate with data scientists and engineers to ensure highquality data ingestion, preprocessing, and feature engineering.
• Model Evaluation & Tuning : Continuously monitor and evaluate model performance, making adjustments to improve accuracy and efficiency.
• Innovation : Stay up-to-date with the latest advancements in AI, LLMs, and cloud technologies, and incorporate new techniques and tools into the development process.
• Collaboration : Work closely with product managers, software engineers, and other stakeholders to integrate AI solutions into products and services.
• Documentation : Maintain comprehensive documentation of models, algorithms, and development processes to ensure transparency and :
• 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 : Bachelors or Masters degree in Computer Science, AI / ML, Data Science, or a related Skills :
• 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.

ref : hirist.tech)