Forward Deployed AI Engineer -Neo4j / Knowledge Graph

Tiger Analytics is seeking a highly experienced Lead AI Engineer to lead the end-to-end AI Engineering workstream for the Luma platform. This is a hands-on technical leadership role responsible for driving the architecture, design, and delivery of enterprise-scale Agentic AI solutions while serving as the primary technical interface for the client.

We are looking for a Forward Deployed AI Engineer to build and deploy enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions. The role involves working directly with customers, rapidly developing POCs/MVPs, and taking solutions into production.

• Build GenAI, RAG, Agentic AI, and AI-powered applications.
• Develop Neo4j Knowledge Graph / GraphRAG solutions – must have.
• Build data and AI pipelines using Databricks and PySpark.
• Develop scalable APIs, microservices, and backend applications using Python or Go.
• Rapidly prototype and deliver POCs/MVPs for customer requirements.
• Deploy AI solutions across AWS, Azure, or GCP.
• Work with LLM frameworks, vector databases, Kubernetes, and cloud-native AI infrastructure.
• Troubleshoot and optimize AI applications for performance, scalability, reliability, and cost.
• Act as a technical consultant and work closely with enterprise customers.

• Neo4j / Knowledge Graph – Mandatory
• Generative AI / LLM / RAG / Agentic AI
• Databricks / Spark / PySpark
• Application Engineering – Python or Go
• Rapid Prototyping / POC Development
• Cloud: AWS / Azure / GCP
• Strong problem-solving and debugging skills
• Self-driven, customer-focused, and comfortable working in ambiguous environments

LangChain, LlamaIndex, LangGraph, AutoGen, GraphRAG, Vector DBs, AWS Bedrock, Azure OpenAI, Kubernetes, Docker, Terraform, vLLM/Triton, PyTorch/Hugging Face.