9+ years of professional experience in building Machine Learning models & systems
2+ years of hands-on experience in how LLMs work & Generative AI (LLM) techniques particularly prompt engineering, RAG, and agents.
Experience in driving the engineering team toward a technical roadmap.
Expert proficiency in programming skills in Python, Langchain / Langgraph and SQL is a must.
Understanding of Cloud services, including Azure, GCP, or AWS
Excellent communication skills to effectively collaborate with business SMEs
Roles & Responsibilities
Develop and optimize LLM-based solutions : Lead the design, training, fine-tuning, and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership : Maintain high-quality, efficient code in Python (using frameworks like LangChain / LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration : Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI / CD processes.
Cross-functional collaboration : Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance : Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.
Continuous innovation : Stay abreast of the latest advancements in LLM research and generative AI, proposing and experimenting with emerging techniques to drive ongoing improvements in model performance.