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.