AI Engineer

About your role-Develop and maintain agentic pipeline using tools such as n8n, Python, JavaScript, Supabase, Pinecone, and NotebookLM.-RAG & Knowledge ManagementBuild vector databases, chunking/embedding strategies, guardrails, and evaluation strategies.MLOps:Implement training and evaluation pipelines, model versioning, and deployment workflows to production environments.Perform prompt engineering, context engineering, database optimization.-Data Integration, Monitoring, and ReliabilityIntegrate multiple data sources and services (e.g., CRM, support tools, product analytics, internal databases).Implement logging, error handling, and monitoring for automation workflows to ensure reliability and traceability.Test and debug flows, APIs, and scripts for production readiness.RequirementsBachelor’s or degree in Computer Science,or a related field.Strong proficiency in Python or JavaScript.Strong ML fundamentals with hands-on experience.Proven experience with LLMs: prompt design, function/tool calling, finetuning/LoRA, RAG.MLOps knowledge — tools like MLflow, artifact/version management, and automated evaluations.Proficiency with Git and Git Flow.Familiarity with agile software development (Scrum, Jira).Good understanding of APIs and backend integration.