CKG Lead Engineer

About Neon - Our Computational Knowledge Graph Platform

Neon is Avathon's proprietary Computational Knowledge Graph (CKG) platform that combines:

1. Knowledge Graph - A network of connected facts, entities, and relationships
2. Computation Graph - Complex analytics and computations defined on top of the knowledge graph

Neon powers decision-intelligence applications across supply chain, manufacturing, and energy domains. It enables multi-hop graph traversals, nested data operations, real-time analytics, and seamless integration with ML/AI pipelines.

About the Role:

We are seeking an experienced CKG Lead Engineer to help design, develop, and scale our Neon platform. In this role, you will work on the full-stack development of our knowledge graph platform, from ontology design and schema modeling to query optimization and Python integration. You will collaborate with data scientists, product managers, and customers to build solutions that leverage Neon's unique computational capabilities.

This is a mid-senior level position (5-8 years experience) that combines technical leadership with hands-on development.

You Will:

Design and implement knowledge graph schemas, ontologies, and data models for complex domains (supply chain, manufacturing BOM, logistics) Develop and optimize IQL (Intermediate Query Language) queries for multi-hop graph traversals, joins, and aggregations Build data ingestion pipelines to populate and maintain knowledge graphs from diverse data sources Implement computational functions and analytics on top of the knowledge graph Integrate Neon with Python/NumPy for advanced analytics and ML model integration Design and build APIs to expose knowledge graph capabilities to downstream applications Optimize query performance for large-scale datasets (1M+ records) Collaborate with product and data science teams to translate business requirements into graph solutions Mentor team members on IQL, graph modeling, and Neon best practices Contribute to platform roadmap and architectural decisions

You'll Have:

5-8 years of software engineering experience, with at least 2 years working with graph technologies or knowledge graphs Strong proficiency in Python programming Experience with graph databases or knowledge graph platforms (Neo4j, Amazon Neptune, TigerGraph, or similar) Understanding of ontology design, schema modeling, and graph data structures Experience with SQL and query optimization Familiarity with REST APIs and web services architecture Experience with cloud platforms (GCP preferred, AWS or Azure acceptable) Strong problem-solving skills and ability to translate complex business requirements into technical solutions Excellent communication skills and ability to work with cross-functional teams BS or MS in Computer Science, Engineering, or related field

Nice to Have:

Experience with RDF, SPARQL, or semantic web technologies Knowledge of NLP/NER pipelines for entity extraction and relationship mining Experience with ML model integration and MLOps Familiarity with supply chain, manufacturing, or BOM data structures Experience with time series data and IoT integration Knowledge of graph algorithms (shortest path, centrality, community detection) Experience with data visualization for graph structures Contributions to open-source graph or knowledge management projects

Key Technologies:

Category Technologies Languages Python (primary), Scala, IQL Graph Platforms Neon/Maana (proprietary), Neo4j concepts Cloud GCP (primary), AWS Lambda for external compute Data SQL, NoSQL, Time Series DBs APIs REST, GraphQL concepts ML Integration TensorFlow, PyTorch, NumPy

Coding Challenge:

As part of the interview process, you will be asked to complete a technical assessment.

Salary Range: $150k-$220k