AI Data Engineer

• Design, build, and deploy agentic AI systems and LLM-powered applications that automate complex analytical and business workflows for Retail clients.
• Develop and orchestrate multi-agent workflows using frameworks such as LangGraph, LangChain, and the Azure AI Agent Service—integrating tools, memory, and reasoning loops.
• Build and optimize retrieval-augmented generation (RAG) pipelines, combining vector search with Neo4j knowledge graphs and graph databases.
• Engineer, evaluate, and fine-tune prompts and LLMs, implementing guardrails, evaluation harnesses, and human-in-the-loop feedback for accuracy and safety.
• Develop backend APIs and services (Python, FastAPI) to serve AI models and agents into production applications.
• Build pipelines using Docker, CI/CD, and Git for continuous deployment on cloud platforms (Azure / GCP/ AWS).
• Implement observability, logging, and evaluation to monitor model quality, latency, and drift of agentic systems in production.
• Develop complex data transformation queries and workflows using SQL, Pandas, or PySpark to process and manipulate large-scale datasets.
• Collaborate with product managers, software developers, and consulting teams to translate business problems into robust, scalable AI solutions.

The Associate is expected to have a knack for seeking out challenging problems and producing their own ideas, which they will be encouraged to brainstorm with their peers and managers. They should be willing to learn new techniques and be open to solving problems with an interdisciplinary approach. They must have excellent coding skills and should demonstrate a willingness to write modular, reusable, and functional code