Forward Deployed AI Engineer – Neo4j, Knowledge Graph

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the complete AI Engineering workstream for the Luma platform.

• Spearhead the architecture, design, and implementation of enterprise-level Agentic AI solutions.

• Act as the main technical point of contact for the client.

• Create and implement enterprise GenAI, RAG, Agentic AI, and Knowledge Graph solutions.

• Collaborate directly with customers.

• Swiftly develop POCs/MVPs and transition solutions into production.

⛳️ Requirements

• Develop GenAI, RAG, Agentic AI, and AI-enabled applications.

• Create Neo4j Knowledge Graph / GraphRAG solutions — essential.

• Construct data and AI pipelines utilizing Databricks and PySpark.

• Design scalable APIs, microservices, and backend applications using Python or Go.

• Quickly prototype and deliver POCs/MVPs based on customer specifications.

• Deploy AI solutions on AWS, Azure, or GCP.

• Engage with LLM frameworks, vector databases, Kubernetes, and cloud-native AI infrastructure.

• Diagnose and enhance AI applications for optimal performance, scalability, reliability, and cost-effectiveness.

• Function as a technical consultant, collaborating closely with enterprise clients.

• Familiarity with Generative AI, LLM, RAG, and Agentic AI.

• Excellent problem-solving and debugging capabilities.

• Self-motivated, customer-oriented, and adept at navigating ambiguous situations.

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

🏝️ Benefits

• Significant career advancement prospects.

• A small, rapidly growing, challenging, and entrepreneurial atmosphere.

• High level of individual accountability.

• Equal employment opportunities safeguarded by applicable law.