GenAI Engineer/Lead 6+years

Location: Bangalore and Chennai We are looking for an experienced Generative AI Engineer to design, develop, and deploy enterprise-scale AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and cloud-based AI platforms. The candidate should have strong software engineering skills and hands-on experience building production-grade GenAI applications. Key Responsibilities Develop and deploy GenAI applications using LLMs, RAG pipelines, AI agents, and multimodal AI solutions. Design prompt engineering strategies, embedding pipelines, semantic search, and knowledge retrieval systems. Build, fine-tune, evaluate, and optimize LLM-based solutions for accuracy, performance, and scalability. Develop AI-powered APIs, microservices, and scalable cloud-native applications. Implement LLM orchestration workflows using modern GenAI frameworks. Collaborate with engineering, data science, and product teams to deliver AI-driven solutions. Apply best practices in AI security, governance, responsible AI, and model monitoring. Required Skills & Experience 612 years of experience in software engineering, AI/ML engineering, or related fields. Strong programming skills in Python with experience in software development practices. Hands-on experience with Generative AI, Large Language Models (LLMs), Prompt Engineering, RAG, AI Agents, and LLM application development. Strong understanding of: LLM architectures, embeddings, vector search, and retrieval techniques Fine-tuning, model evaluation, and optimization approaches AI workflow orchestration and agent-based architectures Experience with GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Hugging Face, and OpenAI-compatible APIs. Experience with vector databases such as FAISS, Pinecone, Weaviate, or Chroma. Experience with PyTorch/TensorFlow and machine learning workflows. Strong knowledge of REST APIs, microservices, distributed systems, and application architecture. Experience with SQL/NoSQL databases. Hands-on experience with cloud platforms (AWS, Azure, or GCP) and AI services. Knowledge of MLOps practices including model deployment, monitoring, CI/CD, Docker, and Kubernetes. Preferred Qualifications Experience building enterprise-grade GenAI solutions in production environments. Experience with open-source LLMs, multimodal AI, and AI automation workflows. Understanding of AI safety, governance, and responsible AI practices. Strong problem-solving skills with the ability to translate business requirements into scalable AI solutions. Education Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related technical discipline preferred .