Generative AI Engineer

About the Role

Elevate Recruitment is seeking a highly skilled and motivated Generative AI Engineer to design, develop, and deploy advanced AI solutions. This senior-level, high-impact role focuses on building production-grade AI systems across various use cases, including content generation, conversational AI, autonomous agents, and intelligent data synthesis, for one of our enterprise AI clients.

Key Responsibilities

• Develop and fine-tune large language models (such as GPT-class, LLaMA-family, Mistral-family, Claude-class models) for domain-specific downstream tasks.
• Design and optimize Retrieval-Augmented Generation (RAG) pipelines using frameworks like LangChain, LlamaIndex, or Haystack.
• Build end-to-end generative AI applications spanning text, code, image, and audio use cases.
• Implement embedding-based retrieval systems using vector databases such as FAISS, Pinecone, Weaviate, or Qdrant.
• Integrate foundation model APIs into scalable production workflows.
• Work with multimodal models and generative systems for image, vision-language, and audio tasks.
• Optimize model latency, throughput, and scalability for production environments.
• Collaborate cross-functionally with ML engineers, data teams, and product stakeholders.
• Stay current with advancements in generative AI research and apply them to real-world systems.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
• Strong hands-on experience in ML/AI engineering, with demonstrated experience in generative AI or LLM-based systems.
• Proficiency in Python and ML frameworks such as PyTorch or TensorFlow.
• Experience using HuggingFace Transformers, LangChain, or similar ecosystems.
• Strong understanding of NLP, transformer architectures, embeddings, and deep learning fundamentals.
• Experience building scalable ML pipelines and deploying models using Docker, Kubernetes, or similar infrastructure tools.
• Familiarity with prompt engineering, fine-tuning strategies, evaluation methodologies, and production model monitoring.

Key skills/competency

• Generative AI
• Large Language Models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Python
• PyTorch
• TensorFlow
• HuggingFace Transformers
• LangChain
• Vector Databases
• ML Pipelines