Source description
About the role
Self-motivated Engineer with a solid grasp of AI/ML fundamentals and a relentless drive for innovation. This role requires an agile builder who can bridge the gap between model research and production-grade software with a product-focused mindset.
Key Responsibilities
Implement high-performance systems leveraging LLMs, Generative AI, and traditional ML to solve enterprise-scale problems. Build and maintain RAG (Retrieval-Augmented Generation) workflows and data pipelines using Python and vector databases. Refine model outputs through prompt engineering, fine-tuning, and latency optimization. Write modular, scalable code and integrate AI services into cloud ecosystems (AWS, Azure, or GCP). Rapidly integrate emerging frameworks like LangChain, LlamaIndex, and Hugging Face into production workflows. Implement automated testing, model monitoring, and "golden datasets" to ensure reliability and safety.
Experience Required
8+ years of hands-on experience in GenAI, Agentic AI, MCP & LLM’s Experience in deploying models in production environments. Why Join Us?
Work in an innovative environment with the business that is shaping the future of data migration. Be part of a dynamic, high-growth environment at NucleusTeq . Competitive salary and comprehensive benefits package .
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