AI Agent Architect / Senior AI Agent Developer
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About the role
Asthe AI Agent Architect / Senior Developer, you will be the core brain behindour flagship enterprise AI platforms. You will transition our systems frombasic LLM wrappers into autonomous, reasoning-capable AI ecosystems. Yourprimary mission is to design and develop advanced Agentic workflows, buildrobust Knowledge Bases utilizing GraphRAG, and engineer complex multi-modaldata processing pipelines. You will ensure our AI solutions deliverexpert-level accuracy, deep contextual understanding, and enterprise-gradesecurity. KeyResponsibilities - AdvancedRAG & Knowledge Base Engineering: Design and implement next-generation RAGsystems using Knowledge Graphs (GraphRAG), vector databases, and semanticsearch. Develop robust OCR pipelines for parsing complex, unstructureddocuments (e.g., contracts, compliance manuals) and multi-modal dataextraction. - AIAgent Architecture: Architect and deploy multi-agent systems (using frameworkslike LangChain, LlamaIndex, or AutoGen) where distinct AI agents can plan,reason, execute tools, and collaborate to solve complex enterprise tasks. - LLMIntegration & Optimization: Evaluate, fine-tune, and deploy various LargeLanguage Models (both closed-source like OpenAI/Anthropic and open-sourcemodels). Optimize prompts and reasoning chains to maximize accuracy andminimize latency. - Backend& Enterprise Integration: Build scalable backend services (primarily inPython, with Java/Spring Boot for legacy or enterprise integrations) to exposeAI capabilities via robust APIs. - Guardrails& Hallucination Mitigation: Implement strict logical guardrails, continuousevaluation frameworks, and "anti-hallucination" mechanisms to ensureall AI outputs are verifiable, strictly grounded in the proprietary knowledgebase, and compliant with enterprise security standards. - Performany ad-hoc duties assignedby the Company as required. RequiredQualifications - Experience:3-5+ years in software engineering, with at least 1.5 - 2 years heavily focusedon LLM applications, generative AI, or complex NLP systems. - AI& Agent Frameworks: Deep hands-on experience with LangChain, LlamaIndex, orsimilar multi-agent orchestration frameworks. - DataParsing & Knowledge Representation: Proven expertise in OCR technologies(e.g., unstructured.io, PaddleOCR) for complex PDF parsing, and strongexperience with Vector Databases (e.g., Milvus, Qdrant, Pinecone) and GraphDatabases (e.g., Neo4j). - ProgrammingMastery: Expert-level proficiency in Python (the primary language for the AIstack). Familiarity with Java/Spring Boot is highly preferred to ensureseamless integration with our existing backend ecosystem. - LanguageProficiency: Professional fluency in English and Mandarin is mandatory toeffectively collaborate with our diverse technical stakeholders and regionalenterprise clients. - ProblemSolving: Strong architectural vision with the ability to translate complexbusiness compliance and expert knowledge into structured AI engineeringpipelines. The"Alpha" Edge (Preferred & Bonus Qualifications) - DomainContext: Previous experience building AI products for Legal, HR, Compliance, orenterprise SaaS。 - ModelDeployment: Experience with local LLM deployment and inference optimization(e.g., Ollama, vLLM, TensorRT-LLM). - MLOps:Familiarity with deploying AI pipelines on cloud infrastructure (AWS/GCP) usingDocker and Kubernetes.
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Company Intel
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