Job Description :

The Digital workforce team is part of Red Hat's Data and AI organization. The team is focused on building and delivering strategic AI agents designed to augment human capabilities, accelerate workflows, and scale operations across the enterprise.

We are seeking a highly experienced Principal Data Scientist to lead our initiatives in natural language processing (NLP), machine learning, and data analytics. The ideal candidate will be passionate about creating and developing applications, particularly within the language sector, and have excellent analytical and machine learning knowledge. The focus of the role will be to transform natural language data and requests into creative and interactive features part of our finance & operations business.

In this role, you will be the voice of Red Hat's technical authority, creating and delivering features and capabilities that help Red Hat's data community and in turn our customers achieve their business and technical goals with Red Hat products effectively.

What will you do?

- Design, develop, and deploy NLP and Generative AI solutions to solve complex business problems.

- Build and enhance AI-powered applications using Large Language Models (LLMs) and modern AI frameworks.

- Develop Retrieval-Augmented Generation (RAG) pipelines by integrating enterprise knowledge sources, embedding models, and vector databases.

- Build and enhance AI agents using LangChain, LangGraph, and other orchestration frameworks to automate business workflows.

- Fine-tune, evaluate, and optimize NLP and LLM-based models for accuracy, scalability, and performance.

- Collaborate closely with finance, operations, engineering, and product teams to understand business requirements and translate them into AI solutions.

- Develop scalable backend services and APIs to support AI applications in production.

- Stay current with emerging advancements in NLP, Generative AI, and Agentic AI, evaluating and adopting new technologies where appropriate.

- Mentor junior data scientists and contribute to AI engineering best practices.

What will you bring?

- 8+ years of professional experience in Data Science, Machine Learning, NLP, or Generative AI with strong proficiency in Python.

- Proven experience designing, building, and deploying NLP and AI/ML applications throughout the complete data science lifecycle.

- Hands-on experience developing LLM-powered applications using models such as GPT, Llama, Claude, or Mistral.

- Experience implementing Retrieval-Augmented Generation (RAG) solutions using embedding models, vector databases, and enterprise knowledge sources.

- Hands-on experience building AI Agents (Agentic AI) using frameworks such as LangChain and LangGraph.

- Experience with embedding models and vector databases such as Pinecone, Chroma, FAISS, Milvus, or Weaviate.

- Strong understanding of prompt engineering, model evaluation, guardrails, hallucination mitigation, and LLM optimization techniques.

- Experience with NLP frameworks such as spaCy and Hugging Face Transformers.

- Working knowledge of machine learning frameworks including PyTorch, TensorFlow, Keras, and TensorFlow Serving.

- Experience developing scalable backend services, REST APIs, and microservices using Python.

- Experience working with AWS or other cloud platforms and container technologies such as Docker and Kubernetes.

- Strong analytical and problem-solving skills with the ability to work effectively in a collaborative, fast-paced environment.

- Passion for staying current with advancements in AI, NLP, and Machine Learning.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Mathematics, Computational Linguistics, or a related field.