AI Developer - LLM Applications, NLP, Ontologies and Knowledge Graphs

Job Summary:

We are seeking an experienced AI Developer with expertise in Large Language Models (LLMs), ontologies, and knowledge graphs to join our team. This role will focus on developing AI-driven solutions that leverage LLMs, ontologies, and semantic knowledge representation to improve knowledge discovery, question-answering, and information retrieval. The ideal candidate is skilled in building scalable and intelligent systems and is passionate about semantic technologies and AI innovation.

Responsibilities: 

• Design, develop, and deploy AI applications that leverage LLMs for tasks such as natural language understanding, question-answering, and contextual content generation.
• Build and maintain knowledge graphs and ontologies to structure and semantically integrate domain-specific knowledge, enhancing data interoperability.
• Collaborate with data scientists, subject matter experts, and engineers to define, model, and implement ontologies that align with business requirements.
• Develop tools and pipelines to ingest, transform, and link data from diverse sources into a unified knowledge graph.
• Use LLMs to augment the knowledge graph, improve data retrieval, and enhance user interactions with the system.
• Implement and optimize NLP models, algorithms, and processing pipelines to ensure efficient, scalable, and accurate performance.
• Research and apply the latest advancements in knowledge representation, LLMs, and semantic search technologies to enhance the application's capabilities.
• Document development processes, architecture, and APIs to ensure maintainability and knowledge sharing.

Education:

• Bachelor’s or Master’s  degree (Preferred) in Computer Science, Data Science, Artificial Intelligence, or a related field.

Qualifications:

• 6-10+ years of professional experience in the related fields including Software Development Life Cycle (SDLC)
• 3 - 5 years of proven experience in developing AI application with large language models (e.g., OpenAI, BERT, GPT-3/4) and natural language processing techniques.
• Strong background in knowledge representation and semantic technologies, including ontologies, RDF, OWL, and SPARQL.
• Proficiency in programming languages like Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
• Excellent analytical and problem-solving skills, with a keen attention to detail.
• Strong communication skills and the ability to work collaboratively in a cross-functional team environment.

Preferred Skills:

• Experience with retrieval-augmented generation (RAG) frameworks or applications.
• Experience with graph databases (e.g., Neo4j, AWS Neptune) and knowledge graph construction.
• Familiarity with data integration, data cleaning, and linking methodologies.
• Knowledge of MLOps practices, cloud platforms (AWS, Azure, GCP), and deployment of AI models in production.
• Familiarity with knowledge base management, content indexing, and search optimization techniques.
• Understanding of data governance, privacy, and security practices in the context of knowledge graphs and AI.