Generative AI Developer/ AI Engineer/ ML Engineer/ Data Scientist

About the job

Work Mode: Remote Experience: 7 years - 10 years Mandatory Skills: AI Application Solution Design, LLM Application Frameworks, Python REQUIREMENTS: • Deep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers) • Should have expert-level prompt engineering skills and proven experience implementing RAG patterns • High proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow). • Experience implementing RAG architectures and prompt engineering. • Strong experience with fine-tuning and distillation techniques and evaluation. • Strong experience using managed AI/ML services on the target cloud platform (e.g., Azure Machine Learning Studio, AI Foundry). • Strong understanding of vector databases (e.g., Weaviate, Neo4j). • Understanding of GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation). • Architect and implement scalable GenAI and Agentic AI solutions end-to-end. • Should be able to write high-quality, production-ready Python code with strong testing and maintainability practices. • Should be able to productionize AI systems on Azure or AWS, ensuring enterprise-grade reliability and performance. • Should be able to build and expose APIs using FastAPI, integrating with databases through an ORM. RESPONSIBILITIES: • Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements. • Mapping decisions with requirements and be able to translate the same to developers. • Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements. • Defining guidelines and benchmarks for NFR considerations during project implementation. • Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers. • Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.

Requirements

• AI Application Solution Design
• LLM Application Frameworks
• Python
• Prompt Engineering
• Managed AI/ML Services

Preferred Technologies

• AI Application Solution Design
• LLM Application Frameworks
• Python
• Prompt Engineering
• Managed AI/ML Services