About your role

-Develop and maintain agentic pipeline using tools such as n8n , Python , JavaScript , Supabase , Pinecone , and NotebookLM .

-RAG & Knowledge Management

• Build 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 Reliability

• Integrate 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.

Requirements

• Bachelor’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).