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.

Requirements

• 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.

Must-Have Skills

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

Good to Have

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

Benefits

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

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Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.

_

• 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.