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Ai engineer – document q&a (llm applications)

Cognizant
Ai engineer
Posted: 30 September
Offer description

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

* 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.
* Experience with Git, collaborative development workflows, and cloud infrastructure (AWS, Azure, GCP, Domino) is a plus.


About Cognizant

At Cognizant you will experience an exciting mix of innovation by design, creativity, collaboration, and efficiency within a framework of stimulating objectives and a passion for delivering the best to our customers.

Our Associates are chosen for their attitude, skills, knowledge, and enthusiasm but above all, their belief that anything is possible.


Equal Opportunity

Cognizant is an equal opportunities employer, and we welcome all applications regardless of race, colour, gender, ethnic origin, nationality, religion or beliefs, disability, age, sexual orientation, political opinions, or trade union membership.

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