Data Science GenAI Engineer

Required Experience

• 4–6 years of overall software engineering or ML experience
• 2+ years of hands-on experience in Generative AI, LLMs, or applied NLP
• Strong programming skills in Python (required); experience with JavaScript/TypeScript is a plus

Technical Skills

• LLM APIs and frameworks: OpenAI-compatible APIs, LangChain, LlamaIndex
• Prompt engineering and RAG architectures
• Vector databases: Pinecone, FAISS, Weaviate, Chroma
• Experience deploying ML/AI solutions in cloud environments (AWS, Azure, or GCP)
• Solid understanding of data structures, APIs, and system design
• Ability to write clean, maintainable, and testable code

Responsibilities

• Design, develop, and deploy Generative AI applications using LLMs (e.g., GPT-based, open-source models)
• Build and optimize prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning pipelines
• Integrate GenAI models into production systems using APIs, microservices, and cloud platforms
• Collaborate with product managers, data scientists, and backend engineers to translate business needs into AI-driven solutions
• Evaluate model performance, mitigate hallucinations, and improve accuracy, safety, and latency
• Implement monitoring, logging, and feedback loops for continuous model improvement
• Stay current with emerging GenAI frameworks, tools, and best practices
• Ensure compliance with security, privacy, and responsible AI guidelines

Preferred Qualifications

• Experience in RAG based applications using LangGraph and FastAPI
• Familiarity with MLOps practices (CI/CD for ML, model versioning, monitoring)
• Knowledge of NLP concepts such as embeddings, transformers, and tokenization