Agentic AI Platform Engineer (Backend / System Architecture)

[Job Description] 1. Agentic Core Engine Development Design and optimize core platform modules, including user context management, short/long-term memory mechanisms, Tool Calling Engine, and Sub-Agent orchestration and collaboration workflows. 2. External Systems Integration & Connectivity Lead the platform's integration architecture with external systems, including Microsoft Teams and enterprise internal services. Establish abstraction layers and API standardization frameworks rather than ad-hoc point-to-point connections. 3. RAG & Knowledge Module Development Design and optimize retrieval pipelines (chunking, embedding, retriever selection), including query rewrite, context construction, and prompt strategies to enhance recall quality across diverse knowledge domains. 4. Backend Services & API Implementation Implement and optimize REST, SSE, and WebSocket services in collaboration with frontend teams to deliver a user-facing, visual Agent Development Environment. 5. System Reliability & Resilience Ensure stability, observability, and fault tolerance of critical system paths while scaling to support rapid user growth. [Required Qualifications] 1. Minimum 3+ years of backend development experience with demonstrated track record of independently owning complete system modules end-to-end. 2. Expert-level proficiency in Python, with solid experience in FastAPI or equivalent mainstream backend frameworks; proven API design and implementation expertise. 3. Strong proficiency in Docker and containerization, capable of building and managing development and deployment environments. 4. Database design and operation competency, with SQL expertise; ORM framework experience is a plus. 5. Proficiency in at least one LLM/Agentic development framework, with practical experience designing Agentic Workflows. 6. Systems thinking mindset, capable of decomposing ambiguous requirements into stable, maintainable, and scalable engineering architecture. [Preferred Qualifications] 1.Demonstrated experience in designing or developing Multi-Agent systems. 2.Hands-on experience with Azure platform and CI/CD practices; familiarity with Azure AI Foundry, Azure OpenAI, and Azure AI Search. 3.Expertise in LLM behavior fine-tuning, Prompt Engineering, Tool Calling error handling, and fallback mechanism design. 4.Experience with Automatic Speech Recognition (ASR/STT), real-time stream processing, or multilingual NLP solutions. 5.Ability to make autonomous technical decisions in contexts lacking clear precedent, with accountability for decision outcomes.