Job Description
JLL, an international real estate management company, is seeking an AI Engineer to join our Work Dynamics Data & Insight COE Team. We are seeking candidates that are self-starters who can work in a diverse and fast-paced environment. We are building a GenAI capability on JLL’s real estate data and are looking for a candidate with hands-on experience in Python, LangChain/Llama Index, Azure OpenAI, RAG pipeline development, and prompt engineering to help design and deploy LLM-powered solutions that deliver measurable business value.
Responsibilities
- Assist in the design and development of Retrieval-Augmented Generation (RAG) pipelines using LangChain or Llama Index to ground LLM responses in JLL’s proprietary data.
- Integrate Azure OpenAI and Azure Cognitive Services APIs into data and application workflows under senior engineer guidance.
- Build and experiment with prompt templates, prompt chains, and few-shot examples to improve LLM accuracy, relevance, and output quality.
- Develop and maintain vector store integrations (Azure AI Search, FAISS, Chroma DB) for semantic search and document retrieval.
- Support the development of AI-powered features including intelligent Q&A systems, summarization tools, and data extraction pipelines on JLL data.
- Assist in fine-tuning and evaluating pre-trained language models and embedding models for domain-specific real estate use cases.
- Write clean, well-tested Python code for AI modules, APIs (FastAPI/Flask), and integration components.
- Support deployment of AI models and services to Azure cloud environments.
- Participate in code reviews, technical discussions, and sprint ceremonies in an Agile delivery environment.
- Document AI solutions, experiment results, prompt strategies, and model evaluation findings clearly for technical and non-technical audiences.
- Monitor deployed AI solutions for performance, accuracy, drift; flag issues and contribute to continuous improvement.
Stay current with rapidly evolving GenAI frameworks, LLM capabilities, and best practices; apply learnings to active projects.
Experience & Education
- 0 to 2 years of relevant experience is desired (internship and project experience considered).
- Having a Bachelors/master’s degree in computer science, Artificial Intelligence, Data Science, Engineering, or a related field from a reputed University
- Strong computer science fundamentals.
- Solid understanding of Software Development Life Cycle (SDLC) includes requirements analysis, design, development, testing, and deployment.
- Strong written and verbal communication skills — able to document AI experiments clearly, explain model behavior to non-technical stakeholders, and collaborate effectively across teams.
- Self-motivated with a strong willingness to learn and rapidly adapt to the fast-evolving GenAI landscape.
- Analytical and detail-oriented — able to evaluate model outputs critically and identify quality or accuracy issues.
Technical Skills & Competencies
- Python — AI/ML engineering, scripting, API development
- Azure OpenAI / Azure Cognitive Services
- LangChain or Llama Index — RAG pipelines, prompt chains
- RAG Architecture — Chunking, Embedding, Vector Retrieval, Reranking
- Vector Stores — Azure AI Search, FAISS, Chroma DB
- Prompt Engineering — Zero-shot, Few-shot, Chain-of-Thought, System Prompting
- ML Fundamentals — Scikit-learn, Model Training, Evaluation, Selection
- API Development — FastAPI / Flask
- Version Control — Git, collaborative development workflows
