Agentic AI Application Engineer （27graduates）

Agentic Ai Application Engineer

We are seeking a highly skilled Agentic AI Application Engineer to design, develop, and deploy next-generation AI-driven applications based on autonomous agent architectures. This role focuses on leveraging cutting-edge technologies such as prompt engineering, LangChain, vector databases, and advanced Python-based backend systems to build intelligent, scalable, and production-ready AI applications.

Key Responsibilities

• Design and develop agentic AI applications capable of autonomous reasoning, planning, and execution.
• Build and orchestrate multi-agent workflows using frameworks such as LangChain (or similar).
• Develop and optimize prompt engineering strategies to enhance LLM performance and reliability.
• Integrate vector databases (e.g., Pinecone, FAISS, Milvus) for semantic search and retrieval-augmented generation (RAG).
• Implement efficient database querying logic (SQL/NoSQL) to support AI workflows and data-driven decision-making.
• Develop backend services and pipelines using Python, ensuring scalability, performance, and maintainability.
• Design and implement APIs and microservices to support AI application integration.
• Collaborate with data engineers, ML engineers, and product teams to deliver end-to-end AI solutions.
• Ensure best practices in model governance, observability, and security for enterprise-grade AI systems.
• Continuously evaluate and adopt emerging technologies in the AI/LLM ecosystem.

Required Skills & Qualifications

• Strong proficiency in Python programming and backend development.
• Hands-on experience with prompt engineering and large language models (LLMs).
• Experience with frameworks such as LangChain or equivalent agent orchestration tools.
• Solid understanding of vector embeddings and experience with vector databases.
• Strong experience in database technologies (SQL/NoSQL) and efficient query design.
• Experience building AI-powered applications (chatbots, copilots, agents, etc.).
• Familiarity with API development and integration (REST/GraphQL).
• Understanding of distributed systems and scalable architecture design.

Preferred Qualifications

• Experience with advanced agent frameworks (e.g., AutoGPT, CrewAI, Semantic Kernel).
• Knowledge of RAG architectures and hybrid search systems.
• Experience with cloud platforms (Azure/AWS) and containerization (Docker/K8s).
• Familiarity with ML Ops / AI Ops practices.
• Exposure to enterprise data governance and security requirements.

Key Competencies

• Strong problem-solving and system design skills.
• Ability to bridge AI technology and business applications.
• Excellent communication and cross-team collaboration skills.
• Proactive mindset in exploring innovative AI solutions.