Generative AI Engineer

• Title:

Generative AI Engineer - Remote

• Engagement:

Hourly contract (independent contractor)

• Location:

Remote

About the Role

One of our enterprise AI clients is seeking a highly skilled and motivated Generative AI Engineer to design, develop, and deploy advanced AI solutions leveraging large language models, multimodal transformers, and generative architectures.

This is a senior-level, hig...h-impact role focused on building production-grade AI systems across content generation, conversational AI, autonomous agents, and intelligent data synthesis use cases.

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

Employment Type

• Full-time position

• Hybrid work model (India-based candidates only)

• Senior experience level

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