AI Engineer – Document Q&A (LLM Applications)

Overview:

We are looking for a results-oriented AI Engineer to join our team developing intelligent Q&A systems powered by large language models. You will help build, test, and optimize pipelines that enable automatic question-answering from large document collections, supporting our mission to surface key knowledge rapidly and accurately.

Responsibilities:

• Build, fine-tune, and evaluate LLM-based Q&A models using frameworks like AWS Bedrock, Langchain, HuggingFace Transformers or OpenAI API.
• Design prompt templates and implement retrieval strategies to increase answer precision and factuality.
• Assist in creating data pipelines for training and testing, including annotation and evaluation tooling.
• Collaborate with senior engineers and product managers to translate user requirements into technical features.
• Participate in error analysis, iterative model improvement, and performance tuning.
• Document code and workflows clearly; follow best practices for reproducibility and code quality.

Requirements:

• Degree in Computer Science, Data Science, or related discipline (or equivalent experience).
• Hands-on experience with machine learning, NLP, or information retrieval projects, preferably with language models.
• Proficiency in Python and familiarity with deep learning/NLP libraries (Langchain, PyTorch, TensorFlow, HuggingFace Transformers).
• Knowledge of vector databases or semantic search concepts is desirable.
• Eagerness to learn, strong problem-solving skills, and ability to work collaboratively in agile teams.
• Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino) is a plus.