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
We are seeking an experienced Lead Knowledge Graph Engineer to help design, develop, and scale our Computational Knowledge Graph (CKG) platform. In this role, you will lead full-stack development, spanning graph storage engines, query optimization, graph processing engine. You will collaborate closely with data scientists, product managers, and customers to build solutions that leverage CKG’s unique computational capabilities.
This is a mid-senior level position (5–7 years of experience) combining technical leadership with hands-on development.
You Will- Model complex domains. Design knowledge graph schemas, ontologies and data models for supply chain, manufacturing BOM and logistics data.
- Build ingestion pipelines. Create and maintain pipelines that bring data from enterprise systems (such as SAP), databases and files into the graph, with the right data quality checks in place. Build the connectors for both IT and OT systems.
- Write and tune graph queries. Develop multi-hop traversals, joins and aggregations in our graph query language (IQL) and in Gremlin, and tune them to run well on datasets with millions of records. Add more graph algorithms for faster multi-hop traversal.
- Build high-performance components. Develop and optimize performance-critical graph and compute components in C++. Improve graph processing engine to support large data set.
- Deliver analytics on the graph. Build computational functions, graph analytics, and connect the graph to Python and NumPy workflows for advanced analytics and ML model integration.
- Expose graph capabilities. Design and build APIs and services that let downstream applications use the knowledge graph.
- Work across teams. Partner with product and data science to turn business problems into graph-based solutions.
- Lead and mentor. Coach engineers on graph modelling, query design, and platform best practices, and contribute to architecture decisions and the technical roadmap.
- 5–7 years of software engineering experience, including at least 2 years hands-on with graph databases or knowledge graphs
- Strong Python skills
- Hands-on C++ experience, ideally on performance-sensitive or systems-level code
- Production experience with a graph database or knowledge graph platform, such as JanusGraph, Neo4j, Amazon Neptune or TigerGraph
- Experience writing and optimizing Gremlin traversals (Apache TinkerPop), preferably on JanusGraph
- A solid grasp of ontology design, schema modeling and graph data structures
- Strong SQL skills and a track record of query performance tuning
- Experience designing and building REST APIs and service-based architectures
- Experience with at least one major cloud platform (GCP preferred; AWS or Azure is fine)
- The ability to turn ambiguous business requirements into clear technical designs
- Clear communication and experience working with cross-functional teams
- A BS or MS in Computer Science, Engineering or a related field, or equivalent practical experience
- Experience with RDF, SPARQL or other semantic web technologies
- Experience with JanusGraph storage and index backends such as Cassandra, HBase, Bigtable or Elasticsearch
- Experience building NLP or named-entity recognition (NER) pipelines for extracting entities and relationships
- Experience with ML model integration and MLOps.
- Experience with graph databases or knowledge graph platforms (Neo4j, Amazon Neptune, TigerGraph, or similar)
- Experience with time-series data or IoT integration
- Working knowledge of graph algorithms such as shortest path, centrality and community detection
- Experience visualizing graph data
- Contributions to open-source graph or knowledge-management projects
What are the benefits and perks at Avathon? Below are some highlights we offer to our U.S. full-time employees -- we'd love to connect and share more!
- Evolving culture with the opportunity to drive new ideas and technology
- Stock Option Grants
- Medical Coverage and Parental Leave Plans
- 401k with Employer Match
- Monthly Technology Allowance
- Newly renovated office space located near Pleasanton, CA -- including fully stocked beverage and snack areas
Contract and temporary roles are not eligible for the above benefits.
CompensationPay Range: $150k - $220k salary annually. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience.
Location: This role is not remote. Candidates must be based in the Bay Area, CA and are expected to report to our Pleasanton office 5 days a week.
Avathon is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.
Avathon is committed to providing reasonable accommodations throughout the recruiting process. If you need a reasonable accommodation, please contact us to discuss how we can assist you.
Skills Required
- 5-7 years of software engineering experience
- At least 2 years of hands-on experience with graph databases or knowledge graphs
- Strong Python skills
- Hands-on C++ experience, ideally with performance-sensitive or systems-level code
- Production experience with a graph database or knowledge graph platform such as JanusGraph, Neo4j, Amazon Neptune, or TigerGraph
- Experience writing and optimizing Gremlin traversals using Apache TinkerPop
- Knowledge of ontology design, schema modeling, and graph data structures
- Strong SQL skills and query performance tuning experience
- Experience designing and building REST APIs and service-based architectures
- Experience with at least one major cloud platform; GCP preferred, AWS or Azure acceptable
- Ability to translate ambiguous business requirements into clear technical designs
- Clear communication and cross-functional collaboration experience
- BS or MS in Computer Science, Engineering, or a related field, or equivalent practical experience
- Experience with RDF, SPARQL, or other semantic web technologies
- Experience with JanusGraph storage and index backends such as Cassandra, HBase, Bigtable, or Elasticsearch
- Experience building NLP or named-entity recognition pipelines
- Experience with machine learning model integration and MLOps
- Experience with time-series data or IoT integration
- Working knowledge of graph algorithms such as shortest path, centrality, and community detection
- Experience visualizing graph data
- Contributions to open-source graph or knowledge-management projects
What We Do
Avathon, a leader in Industrial AI, extends the life of critical infrastructure while advancing the journey toward full autonomy. Avathon’s Industrial AI platform empowers commercial and government customers with scalable, secure, and value-driven solutions that enhance efficiency and resilience across heavy industry.
