Pay not posted
Forward Deployed AI Engineer -Neo4j / Knowledge Graph
First seen · open on Workable as of
Pay not postedUSRemoteFull-time
Lead end-to-end AI engineering for the Luma platform, shaping and delivering enterprise-scale Agentic AI solutions as a hands-on technical lead and primary client interface.
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At a glance
Posted base pay
Not posted
Median $190K
Senior FDE postings1,849 postings · middle 50% of posted pay$160K–$220KThe work
Builds what the customer runs
Balance Mostly building
Project stages
- Pre-sales (not covered)
- Proof of concept
- Implementation
- Operations (not covered)
- Coding
- Writes production code
- Builds for
- External customers
- Level
- Senior
- Role
- Technical lead
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The job description from Tiger Analytics
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.
View posting at Tiger Analytics
About Tiger Analytics
Global AI and advanced analytics consulting firm delivering data strategy, data engineering, AI/ML, application engineering, business intelligence, and MLOps services.
5000+ people
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