Generative AI Engineer

Job description

We are looking for a Sr.GenAI Engineer, who will lead the design, development, integration, and deployment of Generative AI solutions — ranging from enterprise chatbots and document summarization systems to AI-powered search, knowledge management, and content generation platforms. You’ll work closely with Data Scientists, DevOps Engineers, and Full-Stack Developers to operationalize scalable GenAI products for our clients.

Responsibilities and Duties

• Lead the solution design and architecture of Generative AI applications based on business needs and technical feasibility.
• Integrate and deploy Large Language Models (LLMs) using open-source (Hugging Face, Llama, Mistral, Falcon) and commercial models (OpenAI, Azure OpenAI, Anthropic, Gemini).
• Build and operationalize RAG (Retrieval-Augmented Generation) pipelines, integrating vector databases (e.g., FAISS, ChromaDB, Pinecone) for contextual enterprise search.
• Perform LLM fine-tuning (Supervised Fine-Tuning (SFT), LoRA, QLoRA) and Continued Pre-training (CPT) on domain-specific data where required.
• Develop APIs and backend services to serve LLM and GenAI functionalities securely and efficiently.
• Integrate cloud-native AI services (AWS Bedrock, Azure AI, Google Vertex AI) into enterprise applications.
• Collaborate with Data Engineers to curate, preprocess, and vectorize data for RAG and AI pipelines.
• Implement MLOps for GenAI, ensuring model versioning, CI / CD, and monitoring for deployed models.
• Develop quick POCs, pilots, and scalable production-ready applications in collaboration with product teams.
• Stay current with the rapidly evolving GenAI ecosystem and assess emerging tools, frameworks, and models for applicability.

Desired Experience & Qualification

Preferred Qualifications