Senior Associate - AI + Full Stack Engineer

We are looking for a Senior Associate, AI + Full Stack Engineer with strong hands-on expertise in Agentic AI, LLM-powered application development, and full stack engineering. The candidate will design, build, and deploy agentic AI systems and LLM-powered applications that automate complex analytical and business workflows for Consumer Products clients. This includes developing and orchestrating multi-agent workflows using frameworks such as LangGraph, LangChain, and Azure AI Agent Service, integrating tools, memory, and reasoning loops. The role involves building and optimizing retrieval-augmented generation (RAG) pipelines combining vector search with Neo4j knowledge graphs and graph databases, modelling and querying graph databases (Neo4j / Cypher) for complex entity relationships, and engineering, evaluating and fine-tuning prompts and LLMs with guardrails, evaluation harnesses, and human-in-the-loop feedback. The candidate will develop backend APIs and services using Python and FastAPI, and build full stack applications with React, FastAPI, and PostgreSQL. Responsibilities also include deploying, scaling, and operating AI workloads on Azure (Azure OpenAI, Azure AI Foundry, Azure Kubernetes Service), building and maintaining MLOps/LLMOps pipelines using Docker, CI/CD, and Git, implementing observability, logging, and evaluation to monitor model quality, latency, and drift in production, and collaborating with product managers, data scientists, and consulting teams to translate business problems into robust, scalable AI solutions. Prior consulting experience is a strong plus.

Key Responsibilities

• Design, build, and deploy agentic AI systems and LLM-powered applications automating complex analytical and business workflows for Consumer Products clients.
• Develop and orchestrate multi-agent workflows using LangGraph, LangChain, and Azure AI Agent Service - integrating tools, memory, and reasoning loops.
• Build and optimize RAG pipelines, combining vector search with Neo4j knowledge graphs and graph databases.
• Model and query graph databases (Neo4j / Cypher) to represent complex entity relationships and power graph-based retrieval and reasoning.
• 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.
• Deploy, scale, and operate AI workloads on Azure (Azure OpenAI, Azure AI Foundry, Azure Kubernetes Service), optimizing for performance, cost, and reliability.
• Build and maintain MLOps/LLMOps pipelines using Docker, CI/CD, and Git for continuous deployment and monitoring of AI services.
• Implement observability, logging, and evaluation to monitor model quality, latency, and drift of agentic systems in production.
• Collaborate with product managers, data scientists, and consulting teams to translate business problems into robust, scalable AI solutions.
• 5-8 years with undergrad and 6 months-3 years with Masters .