Lead Engineer, Computational Knowledge Graph

Avathon

• $150K — $220K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-8 years of software engineering experience, with a focus on graph technologies.
  • Strong proficiency in Python programming.
  • Experience with graph databases, such as Neo4j or Amazon Neptune.
  • Understanding of ontology design and schema modeling.
  • Familiarity with REST APIs and cloud platforms, preferably GCP.
  • Excellent problem-solving and communication skills.
  • BS or MS in Computer Science or a related field.

Responsibilities

  • Design and implement knowledge graph schemas and data models.
  • Develop and optimize IQL queries for complex graph traversals.
  • Build data ingestion pipelines for knowledge graph maintenance.
  • Implement computational functions for graph analytics.
  • Integrate Neon with Python for advanced analytics.
  • Design and build APIs for knowledge graph capabilities.
  • Mentor team members on graph modeling and best practices.

Benefits

  • Work on groundbreaking AI solutions in a high-growth startup environment.
  • Collaborate in a team that values agility and professional growth.
  • Contribute to projects that drive real change across industries.
  • Opportunity to mentor and lead as part of a collaborative team.
Full Job Description
About the Role

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.
You'll Have
  • 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
Preferred Qualifications
  • 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
Benefits & Perks

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.
Compensation

Pay 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.

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