Role: Principal GenAI Developer
Location: NYC (Hybrid)
Full-time Hiring
Experience: 8+ years only
What We’re Looking For
8-13 years of experience in ML/AI systems
2+ years hands-on experience with LLMs (RAG, agents, prompt engineering)
Strong proficiency in Python, LangGraph, and SQL
Experience deploying GenAI systems on AWS / Azure / GCP
Good to Have - Knowledge Graph Expertise
Design and scale enterprise Knowledge Graph architectures
Develop ontologies, taxonomies, and semantic data models
Implement entity resolution, relationship extraction, and graph enrichment
Experience with Neo4j, Amazon Neptune, or similar graph databases
Strong hands-on experience with Cypher (or similar graph query languages)
Build hybrid retrieval systems combining Knowledge Graphs + vector databases
Integrate structured graph reasoning with LLMs to reduce hallucination and improve explainability.
Roles & Responsibilities
Develop and optimize LLM-based solutions: Lead the design and deployment of large language models, leveraging techniques like prompt engineering, retrieval-augmented generation (RAG), and agent-based architectures.
Codebase ownership: Build and maintain/review high-quality, efficient code in Python (using frameworks like LangChain/LangGraph) and SQL, focusing on reusable components, scalability, and performance best practices.
Cloud integration: Aide in deployment of GenAI applications on cloud platforms (Azure, GCP, or AWS), optimizing resource usage and ensuring robust CI/CD processes.
Cross-functional collaboration: Work closely with product owners, data scientists, and business SMEs to define project requirements, translate technical details, and deliver impactful AI products.
Mentoring and guidance: Provide technical leadership and knowledge-sharing to the engineering team, fostering best practices in machine learning and large language model development.