Generative AI Engineer

5 days ago

Hyderabad, India Linkfields Innovations (Pty) Ltd Full time

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 Bachelor’s or Master’s Degree in Computer Science, AI/ML, Data Science, or a related technical discipline. Minimum 4 years of AI/ML engineering experience , with at least 2+ years hands-on in Generative AI and Agentic AI implementation . Proven experience with LLM frameworks and libraries like Hugging Face Transformers, LangChain, LlamaIndex , etc. Hands-on experience with LLM deployment frameworks such as TGI (Text Generation Inference), vLLM, Ollama, BentoML . Expertise in building RAG pipelines and integrating vector databases (FAISS, ChromaDB, Pinecone, Weaviate). Solid experience with Python for AI/ML model development, API development (FastAPI, Flask), and automation. Familiarity with cloud AI platforms (AWS Bedrock, Azure OpenAI, GCP Vertex AI, Databricks). Experience in containerization (Docker) and deploying AI services with MLOps pipelines and CI/CD integration. Strong understanding of AI security, prompt engineering, data privacy, and model governance practices. Excellent problem-solving, critical-thinking, and cross-functional collaboration skills. Preferred Qualifications Experience with open-source LLM fine-tuning tools like PEFT, LoRA, QLoRA, Hugging Face PEFT library . Familiarity with Generative AI frameworks for images, audio, or video (e.g., Stable Diffusion, Whisper, Bark). Experience integrating GenAI into enterprise chatbots, documentation search, summarization systems, or code generation tools . Working knowledge of AWS Lambda, API Gateway , and serverless AI application development. Experience with Streamlit, Gradio, or Dash for rapid prototyping of GenAI applications. Cloud certifications in AWS AI/ML , Azure AI Engineer , or GCP AI Engineer tracks.

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