Job Description:
- Design and develop enterprise grade Generative AI solutions using Python and modern AI frameworks
- Build AI applications using LLMs embeddings prompts function calling tool usage and agentic AI patterns
- Implement Retrieval Augmented Generation RAG pipelines for enterprise knowledge retrieval and generation use cases
- Design end to end AI solutions covering
- o Data ingestion
- o Data processing
- o Retrieval
- o Generation
- o Evaluation
- Work with Agentic AI frameworks such as CrewAI LangChain LangGraph LlamaIndex AutoGen and Langfuse
- Apply prompt engineering strategies to improve LLM accuracy reliability and usability
- Evaluate the suitability of fine tuning vs RAG based on business and technical requirements
- Support LLM fine tuning workflows including instruction tuning and supervised fine tuning
- Manage data preparation for fine tuning including train validation splits data quality checks and contamination prevention
- Deploy AI workloads on cloud platforms such as Azure AWS or GCP
- Containerize AI applications using Docker and work with basic Kubernetes concepts
- Apply model engineering best practices for scalable reliable and production ready AI systems
Key Responsibilities:
- We are looking for a highly skilled Generative AI Engineer Senior Technologist with strong hands on experience in Python Large Language Models RAG Agentic AI fine tuning and cloud deployment
- The ideal candidate should have a deep understanding of LLM architectures at a systems level and the ability to design build deploy and evaluate end to end AI solutions for enterprise use cases
- This role requires strong engineering capability problem solving skills and practical exposure to modern AI frameworks cloud native deployment and model engineering concepts
Preferred Skills:
Technology->AI-Responsible AI->Responsible AI->explainable ai,Technology->AI-AI Engineering->LLMOps
