Forward Deployed AI Engineer -Neo4j / Knowledge Graph

Tiger Analytics Inc.

About The Position

Tiger Analytics is seeking a Forward Deployed AI Engineer to build and deploy enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions. This role involves working directly with customers, rapidly developing POCs/MVPs, and taking solutions into production. The position offers significant career development opportunities as the company grows and provides a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.

Requirements

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

Nice To Haves

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

Responsibilities

Build GenAI, RAG, Agentic AI, and AI-powered applications.
Develop Neo4j Knowledge Graph / GraphRAG solutions.
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.