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Forward Deployed AI Engineer -Neo4j / Knowledge Graph

πŸ“… Sep 1
Neo4jKnowledge GraphsGraphragGenerative AI
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πŸ“œ Description

  • Build and deploy GenAI, RAG, agentic AI, and knowledge graph applications.
  • Develop Neo4j knowledge graph and GraphRAG solutions.
  • Create data and AI pipelines with Databricks and PySpark.
  • Build scalable APIs, microservices, and backend applications using Python or Go.
  • Rapidly prototype customer solutions and take POCs/MVPs into production.
  • Deploy and optimize AI applications across cloud platforms, focusing on performance, reliability, scalability, and cost.

πŸ› οΈ 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.
  • Neo4j / Knowledge Graph – Mandatory
Full 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.

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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