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Lead Engineer, Computational Knowledge Graph

Avathon · Pleasanton, California, United States · Posted May 26, 2026

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Who We Are Why Join Us

Avathon is the leading Industrial AI autonomy platform, helping customers across heavy industries -- energy, mining, manufacturing, aerospace, defense, and logistics -- accelerate the journey toward autonomous operations. Our platform is built on a Computational Knowledge Graph foundation that contextualizes and connects operational data across siloed systems, bringing together time series, structured, unstructured, and machine vision data to power AI-driven applications in asset performance management, supply chain intelligence, visual AI, and global trade management. With capabilities spanning digital twins, normal behavior modeling, natural language processing, and computer vision, Avathon delivers real-time predictive intelligence and agentic decision-making at industrial scale.

Cutting-Edge AI Innovation -- Join a team at the forefront of AI, developing groundbreaking solutions that shape the future. High-Growth Environment -- Thrive in a fast-scaling startup where agility, collaboration, and rapid professional growth are the norm. Meaningful Impact -- Work on AI-driven projects that drive real change across industries and improve lives.

Learn more at: avathon.com

About Neon -- Our Computational Knowledge Graph Platform

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

Knowledge Graph -- A network of connected facts, entities, and relationships

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 (5-7 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

5-7 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

Preferred Qualifications

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

Interview Process

As part of the interview process, you will be asked to complete a technical assess…

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