Forward Deployed AI Engineer -Neo4j / Knowledge Graph

Tiger Analytics Inc.; United States; On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Career development opportunities

Entrepreneurial environment

Job summary

Tiger Analytics Inc. seeks a Lead AI Engineer to spearhead the end-to-end AI Engineering workstream for the Luma platform, delivering enterprise-scale GenAI, knowledge graph, and RAG solutions.

This hands-on leadership role interfaces with clients and drives architecture, design, and production deployment. You will build Neo4j knowledge graphs, Databricks pipelines, and scalable APIs using Python or Go, delivering rapid POCs/MVPs across AWS, Azure, or GCP, while advising customers and guiding

Qualifications

• Must have Neo4j / Knowledge Graph
• Expertise in Generative AI / LLM / RAG / Agentic AI
• Experience with Databricks, Spark, PySpark
• Application engineering capabilities in Python or Go
• Rapid prototyping / POC development
• Cloud deployment across AWS / Azure / GCP
• Strong problem-solving and debugging skills
• Self-driven, customer-focused in ambiguous environments

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 apps in Python or Go
• Rapidly prototype and deliver POCs/MVPs for customers
• Deploy AI solutions across AWS, Azure, or GCP
• Work with LLM frameworks, vector databases, Kubernetes, and cloud-native infra
• Troubleshoot and optimize AI apps for performance, scalability, reliability, cost
• Act as technical consultant for enterprise customers

Skills

Knowledge Graph

Generative AI/LLM/RAG

Databricks/ Spark/ PySpark

Python/Go

POC Development

Cloud AWS/Azure/GCP

LLM frameworks/Vector DBs

Problem solving

Tools

Neo4j

Databricks

PySpark

Kubernetes

Docker

Job description

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.

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.

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.

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.