Forward Deployed AI Engineer – Neo4j, Knowledge Graph

🕒 September 2

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 11%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Tiger Analytics

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🏥 Healthcare

📦 Logistics

📣 Marketing

Healthcare • Logistics • Marketing

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

📋 Description

• Lead the end-to-end AI Engineering workstream for the Luma platform • Drive architecture, design, and delivery of enterprise-scale Agentic AI solutions • Serve as the primary technical interface for the client • Build and deploy enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions • Work directly with customers • Rapidly develop POCs/MVPs and take solutions into production

🎯 Requirements

• Build GenAI, RAG, Agentic AI, and AI-powered applications • Develop Neo4j Knowledge Graph / GraphRAG solutions — mandatory • 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 • Experience with Generative AI, LLM, RAG, and Agentic AI • 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 • Small, fast-growing, challenging and entrepreneurial environment • High degree of individual responsibility • Equal employment opportunities protected by applicable law