Lead Engineer

Experience: 6–10 years | Function: Data Science & AI

About the Role

We're looking for data science and AI engineering with 6–10 years of experience across core data science, Machine Learning, Generative AI, and Agentic AI. You'll build everything from statistical models to LLM-powered and autonomous agent solutions, driving real business impact while mentoring the team.

Key Responsibilities

• Design experiments and apply statistical techniques to extract insights from large datasets
• Build and deploy ML models (clustering, decision trees, neural networks, simulation) for predictive use.
• Build Generative AI solutions involving prompt engineering, fine-tuning and RAG pipelines using LLMs
• Design agentic AI systems involving multi-agent orchestration, tool calling, autonomous workflows.
• Host and deploy models and agents as scalable API-ready services
• Champion explainable and responsible AI practices across all solutions
• Mentor junior data scientists and present technical work clearly to non-technical stakeholders

Requirements

• 6–10 years of experience in data science, machine learning, or applied AI, with production deployment experience
• Advanced proficiency in Python and SQL for data manipulation and analysis at scale with solid statistical and ML foundation
• Mentoring the team.
• Hands-on experience with LLMs including RAG, prompt engineering, fine-tuning and agentic frameworks
• Practical experience building agentic AI systems involving tool calling and autonomous workflows.
• Familiarity with vector and orchestration frameworks like LangChain, LangGraph, LlamaIndex
• Experience with model and agent hosting (MLOps/LLMOps) and API deployments
• Excellent communication skills with ability to explain technical work to non-technical audiences
• Strong analytical and problem-solving mindset and comfortable working in a fast-paced ambiguous environment