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Role Description

We are currently looking to hire an AI Engineer Report automation / AI questionnaire to work with us remotely.

What you will be doing:

• Designs, develops, and deploys end-to-end artificial intelligence systems with a focus on generative AI, large language models, and computer vision.
• Owns the full AI lifecycle independently—from data preparation and model development to packaging, serving, scaling, and monitoring models in production.
• Builds scalable AI solutions such as chatbots, copilots, predictive systems, intelligent automation, and vision-based applications, leveraging Snowflake as part of the data and analytics environment.

Your duties will also involve:

• Artificial Intelligence, Machine Learning, and Deep Learning
• Generative AI and Large Language Models (LLMs)
• Prompt engineering, fine-tuning, and model evaluation
• Computer Vision (image classification, object detection, OCR)
• NLP, neural networks, and predictive modeling
• Python and AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, LlamaIndex)
• Packaging, serving, and scaling models using APIs, microservices, and batch or real-time inference architectures
• Retrieval-Augmented Generation (RAG)
• Snowflake (data modeling, analytics, and AI integrations)
• Model deployment, monitoring, and optimization (MLOps)
• Cloud platforms and AI APIs
• Ability to work independently and take full ownership of AI solutions end to end

Qualifications

• The ideal experience range for this role is 2 to 3 years.
• Strong hands-on experience in AI, Machine Learning, and Deep Learning in production use cases.
• Practical experience working with Generative AI and Large Language Models (LLMs).
• Experience in prompt engineering, fine-tuning, and evaluating LLM-based solutions.
• Solid background in Computer Vision (image classification, object detection, OCR).
• Experience with NLP, neural networks, and predictive modeling.
• Strong programming skills in Python and experience with frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, or LlamaIndex.
• Experience building AI applications such as chatbots, copilots, automation tools, or vision-based systems.
• Knowledge of Retrieval-Augmented Generation (RAG) architectures.
• Experience packaging and serving models using APIs, microservices, and real-time or batch inference.
• Experience working with data platforms such as Snowflake.
• Understanding of model deployment, monitoring, and optimization (MLOps).
• Familiarity with cloud platforms and AI service APIs.
• Ability to work independently and own AI solutions end to end, from data preparation to production deployment.