Senior LLM Engineer – Agentic AI Platform

Your responsibilities, Design and implement deterministic workflows ensuring consistent and reliable LLM outputs, Develop evaluation frameworks to measure and validate deterministic model behavior, Address core LLM challenges, including improving mathematical reasoning accuracy and output reliability, Implement guardrails using structured outputs and Pydantic-based input/output validation, Design and manage tool-calling mechanisms for agent-based architectures, Build and optimize LLM pipelines using parameter-efficient fine-tuning techniques (LoRA, QLoRA), Apply knowledge of training dynamics, loss functions, and optimization strategies, Implement and maintain Model Context Protocol (MCP) architecture, Develop and deploy LLM-powered services using FastAPI or Flask, Build lightweight front-end interfaces using Streamlit for AI-driven workflows, Design RESTful APIs, manage HTTP methods, and implement WebSocket-based communication, Oversee API lifecycle management, versioning, and performance optimization, Integrate structured and semantic data storage solutions (SQL, NoSQL, vector databases), Implement semantic search and retrieval pipelines leveraging vector databases