Must-Have Skills
Python development with solid software engineering fundamentals
Hands-on experience building RAG (Retrieval-Augmented Generation) pipelines
Experience developing Agentic AI workflows with state management and tool orchestration
Solid expertise in FastAPI for AI microservices
Knowledge of Google GECX
Experience with Prompt Engineering, Pydantic, JSON schema, and structured extraction
Experience with LLM APIs, HTTP clients, testing, debugging, and observability

Key Responsibilities
Design and develop custom RAG pipelines including chunking, embeddings, hybrid search, re-ranking, and retrieval.
Build agentic workflows with working memory, state machines, tool execution, and deterministic orchestration.
Optimize prompts, context engineering,



and token usage for performance and cost efficiency.
Develop transparent, debuggable AI microservices using FastAPI and Python.
Implement structured data extraction using Pydantic and JSON schemas.
Build unit tests, RAG regression tests, and debugging frameworks for AI components.
Monitor and optimize AI systems using tracing, logging, and latency/token metrics.
Collaborate with cross-functional teams to deliver scalable, enterprise-grade AI solutions.

Experience Required:

Python development with hands-on experience in RAG, Agentic AI, FastAPI, and LLM-based application development.

📌 Ai Developer Brampton
🏢 Ju0026M Group
📍 Brampton