Senior AI Engineer

Qualifications Bachelor's Degree in Computer Science, Mathematics, Applied Physics, Data Science, or a related field 2 to 4 years in data engineering, platform engineering, MLOps, or operations-focused technical role. Hands-on experience building automation solutions or data pipelines in a production environment. Exposure to AI/ML tooling, agentic frameworks, or LLM-based applications is a strong plus. Comfortable working in ambiguous environments, able to identify problems and propose solutions independently. Plus Points Proficient in Python, Pandas, Polars, and Apache Spark. Hands-on experience with LangChain, LangGraph, RAG pipelines, and prompt engineering. Familiar with PostgreSQL, Apache Iceberg Understand end-to-end AI architecture - RAG, agentic systems, multi-model workflows, APIs, and production deployment. Knowledgeable in ethical AI, bias mitigation, transparency, AI governance, and enterprise regulatory considerations. Strong grasp of data modeling, feature stores, dimensional modeling, and dataset structure for ML pipelines.