AI/ML Engineer (Generative AI & LLMs)

AI/ML Engineer (Generative AI & LLMs) The ideal candidate will have strong experience with transformer-based Models, LLM engineering, scalable backend systems, and cloud-based AI infrastructure. The ideal candidate will have strong experience with transformer-based models, LLM engineering, scalable backend systems, and cloud-based AI infrastructure Key Responsibilities AI / ML Development: Design and build AI-powered applications using transformer-based Large Language Models (LLMs) . Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for context-aware AI systems. Implement prompt engineering techniques to improve LLM accuracy and performance. Apply techniques to reduce hallucinations and improve model reliability . LLM Engineering: Build end-to-end LLM pipelines using Lang Chain or Llama Index . Integrate vector databases for semantic search and contextual retrieval . Develop AI workflows involving multiple model interactions and tool integrations . Contribute to improving LLM evaluation and monitoring frameworks . Backend & Platform Development: Develop scalable Python-based backend services for AI applications. Design and implement REST APIs for AI-driven systems. Build systems using microservices architecture and distributed systems principles . Data Infrastructure & Scalability: Implement scalable pipelines using Redis, message queues (Pub/Sub or Kafka) , and caching mechanisms. Architect backend systems capable of handling large-scale user traffic and AI workloads . Ensure system performance, reliability, and efficient resource utilization. Cloud & Deployment: Deploy and manage AI systems on Google Cloud Platform (preferred) or AWS/Azure . Work with cloud-native infrastructure for model deployment, scaling, and monitoring . Collaboration: Collaborate with product managers, data scientists, and engineering teams to translate business requirements into AI solutions. Participate in architecture discussions and technical decision-making . Continuously explore and adopt latest advancements in AI and Generative AI technologies . Required Skills & Qualifications EDUCATION: Bachelor’s or Master’s degree in: Computer Science Artificial Intelligence. Machine Learning. Data Science. or equivalent practical experience in AI/ML engineering. Experience: 2+ years of experience working with AI/ML or LLM-based systems . AI / Machine Learning: Strong understanding of Transformer architecture . Experience working with Large Language Models (LLMs) . Knowledge of RNNs, LSTMs, and the evolution toward transformer-based architectures . Understanding of Reinforcement Learning from Human Feedback (RLHF) . LLM Engineering: Prompt engineering. Retrieval-Augmented Generation (RAG) pipelines. Experience with Lang Chain or Llama Index . Experience working with vector databases . Backend & Systems: Python programming . Building REST APIs . Microservices architecture. Distributed systems design. Data & Infrastructure: Redis. Message queues such as Google Pub/Sub or Kafka . Designing scalable backend systems . Cloud Platforms: Google Cloud Platform (preferred) . Experience with AWS or Azure also acceptable. Good to Have Experience building AI developer tools or AI platforms . Knowledge of test automation frameworks . Experience with LLM evaluation frameworks . Familiarity with MLOps pipelines and model lifecycle management.