JG
Jade Global
AI Engineer
AI/ML Engineer
On-siteSeniorAI Engineerposted 10mo ago
Role summaryAI-generated
This role demands expertise in building and deploying advanced GenAI applications with a focus on multi-agent systems and RAG pipelines, requiring hands-on experience in productionizing AI solutions across cloud platforms while ensuring scalability and compliance. The candidate will collaborate on cutting-edge projects involving LLMs, agentic workflows, and intelligent UI integrations to drive innovation in enterprise-grade AI solutions.
Skills required
Llm integrationRag pipelinesAgentic architecturesFastapi flaskPrompt engineeringMcp a2a systemsGenai frameworksCloud deploymentResponsible aiAILLMsGenerative AIAzureAgentic AIRAGLangChainLlamaIndexFastAPIFlaskCloud computingPythonDeep learningNatural language processingHTMLCSSJavaScriptReactApi designMLOpsAWS
About this role
AI/ML Engineer2
Key Responsibilities
- Build and deploy LLM-based GenAI applications end-to-end
- Work with multiple LLMs (OpenAI/Azure OpenAI, Gemini, Claude, LLaMA, Mistral)
- Design and implement agentic and multi-agent systems using MCP and A2A
- Develop RAG pipelines and document intelligence solutions
- Use modern GenAI frameworks (LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, Google ADK)
- Build AI backend services using FastAPI and Flask
- Develop and integrate chat UIs, copilots, and dashboards with AI APIs
- Productionize, deploy, and monitor AI systems on cloud platforms
- Ensure performance, security, scalability, and Responsible AI compliance
Required Skills
- Strong Python programming with FastAPI and Flask
- Solid understanding of ML, Deep Learning, NLP, and GenAI concepts
- Hands-on experience with LLMs, embeddings, and prompt engineering
- Experience designing agentic systems with MCP / A2A
- Expertise in RAG architectures and vector databases (FAISS, Pinecone, Weaviate, Chroma, Milvus)
- Working knowledge of front-end technologies: HTML, CSS, JavaScript, Stremlit; React preferred
- API design and integration (REST / WebSockets)
- Strong deployment & MLOps experience: Azure / AWS / GCP, Docker, Kubernetes, CI/CD, MLflow / Azure ML / SageMaker / Vertex AI
Good to Have
- Fine-tuning open-source LLMs (LoRA, PEFT, Hugging Face)
- Experience with autonomous agents and async workflows
- Exposure to RPA + Agentic AI integration
- Knowledge of AI governance, monitoring, and security
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