Senior AI Developer

Architect and Implement AI Systems: Lead the design and development of end-to-end GenAI solutions, including RAG pipelines and AI agents, from idea to production deployment. Knowledge Graph Development: Design, develop, and maintain large-scale knowledge graphs using Neo4j to structure complex, multi-source enterprise data (both structured and unstructured). GraphRAG Implementation: Build sophisticated GraphRAG pipelines that integrate vector databases and knowledge graphs to ground AI responses in factual, verifiable information and mitigate hallucinations. Model Integration and Optimization: Collaborate with data scientists and ML engineers to prepare data and infrastructure for fine‑tuning open‑source or proprietary Large Language Models (LLMs) and optimizing them for performance and efficiency. Data Pipeline Development: Set up scalable data pipelines for data ingestion, embedding generation, preprocessing, and continuous model training/retraining. Technical Leadership & Collaboration: Partner with cross‑functional teams (e.g., data engineers, product managers, business stakeholders) to translate complex business needs into robust, scalable AI architectures and provide technical guidance to junior developers. Innovation & Best Practices: Stay current with the latest advancements in GenAI, graph databases, and MLOps, advocating for and implementing best practices in CI/CD, testing, and responsible AI. Required Skills & Qualifications Experience: 7+ years of experience in software development or AI engineering, with a strong portfolio of production‑ready AI projects. Programming Proficiency: Expert‑level proficiency in Python and related AI/ML frameworks (e.g., PyTorch, TensorFlow, LangChain, LlamaIndex). Graph Database Expertise: Strong hands‑on experience with graph databases, especially Neo4j , including data modeling, Cypher query language, and graph algorithms. GenAI & RAG Knowledge: Deep understanding and practical experience with GenAI concepts, LLMs, prompt engineering, embeddings, and building RAG systems. Cloud & Infrastructure: Experience in deploying and optimizing models in cloud environments (GCP) and managing project infrastructure. Problem‑Solving: Excellent analytical and problem‑solving skills, with the ability to tackle complex, novel challenges in AI development. Education: Bachelor's or master’s degree in computer science, Data Science, Engineering, or a related technical field. CLOUD ANALYTICS TECHNOLOGIES is an equal opportunity employer inclusive of female, minority, disability and veterans, (M/F/D/V). Hiring, promotion, transfer, compensation, benefits, discipline, termination and all other employment decisions are made without regard to race, color, religion, sex, sexual orientation, gender identity, age, disability, national origin, citizenship/immigration status, veteran status or any other protected status. CLOUD ANALYTICS TECHNOLOGIES will not make any posting or employment decision that does not comply with applicable laws relating to labor and employment, equal opportunity, employment eligibility requirements or related matters. Nor will CLOUD ANALYTICS TECHNOLOGIES require in a posting or otherwise U.S. citizenship or lawful permanent residency in the U.S. as a condition of employment except as necessary to comply with law, regulation, executive order, or federal, state, or local government contract. #J-18808-Ljbffr