# Forward Deployed AI Engineer -Neo4j / Knowledge Graph at Tiger Analytics

> Remote · United States · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/workable%3Atiger-analytics%3A945C6A4A52 (read 2026-11-05).

## Facts (observed)

- Company: [Tiger Analytics](https://alderhq.app/companies/tiger-analytics)
- Location text: United States
- Where it can be done from (inferred): Remote · United States (evidence: "Location: United States")
- Posted: 2026-09-01 (66 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://apply.workable.com/j/945C6A4A52
- Skills listed (inferred): Python, AWS, GCP, Azure, Kubernetes, Docker, Terraform, Spark, PyTorch, LLMs, Distributed systems

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (United States, n 608): p25 $183k, median $225k, p75 $280k

## Description (the employer's text)

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.

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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/workable%3Atiger-analytics%3A945C6A4A52 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.