Data Science GenAI Engineer

About the role

4–6 years of overall software engineering or ML experience. LLM APIs and frameworks (e.g., OpenAI-compatible APIs, LangChain, LlamaIndex) Vector databases (e.g., 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.

What you'll do

• 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

What you need

• 4–6 yrs of experience
• LLMs
• Machine learning
• NLP
• Prompt engineering
• AWS
• MLOps
• Any graduate

Good to have

• Python
• JavaScript
• TypeScript
• GCP
• Data structures
• System design