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Squirro

Senior Software Engineer - Knowledge Graph & GraphRAG

Posted 16 Days Ago
In-Office or Remote
Hiring Remotely in New York, NY
Senior level
In-Office or Remote
Hiring Remotely in New York, NY
Senior level
Lead development and productization of knowledge-graph features and GraphRAG modules. Build graph-native agent tooling (SPARQL, graph search, traversal), extend ontologies and workflow modeling, optimize performance, and collaborate with product, engineering, and sales to ship scalable solutions and maintain documentation and training.
The summary above was generated by AI

At Squirro, we build solutions that bring structure, clarity, and insight to messy real-world data — used daily by leading organizations like the Bank of England, Standard Chartered, and the European Central Bank. We believe the next leap in enterprise AI comes from combining knowledge graphs with generative AI.

We’re looking for a hands-on Senior Software Engineer to help advance our knowledge-graph capabilities and lead the next phase of GraphRAG — retrieval and generation grounded in structured knowledge. Building on an established foundation and a clear roadmap, you’ll mature emerging capabilities into reliable product features, build graph-native tools for AI agents, and turn ontologies and workflows into living parts of the platform.

What You’ll Do

  • Advance our knowledge-graph platform: Build on our existing knowledge-graph foundation to mature and productize integration capabilities — evolving established functions and pipelets into reliable, configurable product features aligned with Squirro’s configuration system.
  • Evolve our GraphRAG approach: Refine and extend our GraphRAG methodologies as a set of collaborating modules — where the graph holds domain facts, acts as an index for better RAG, and encodes procedural, agentic knowledge.
  • Expand our graph-native agent tooling: Grow our library of agentic GraphRAG tools — retrieving ontology schemas via SPARQL, graph search and subgraph extraction, graph traversal, and executing custom SPARQL.
  • Deepen agentic workflows: Build on our work modelling workflows in the graph — extending the BBO ontology, exploring transparent BPMN, and making tool libraries available to agents via GraphRAG.
  • Keep raising the bar: Continuously benchmark and optimize performance, surface and resolve edge cases, and keep documentation, training material, demos, and sales guidelines current as the platform grows.
  • Collaborate: Work closely with product, engineering, and sales to identify use cases and ship solutions that work at scale.

What You Bring

  • Strong experience building and scaling backend systems in Python — ideally data-heavy.
  • Hands-on knowledge of knowledge graphs and semantic web technologies: RDF, SPARQL, ontologies (OWL/SKOS), and triplestores.
  • Familiarity with Retrieval-Augmented Generation, LLMs, embeddings, and agentic / tool-using AI patterns (or the curiosity to go deep fast).
  • Solid grasp of distributed systems fundamentals.
  • Bonus: experience with taxonomy/ontology management platforms, GraphRAG, or BPMN/workflow modeling.
  • A pragmatic mindset and comfort in a collaborative, fast-moving environment where ideas quickly turn into production.

Why Join Us

  • Impact: Your work won’t disappear into a pipeline — you’ll see it used daily by some of the world’s leading organizations.
  • Growth: Work on cutting-edge problems in AI, search, and knowledge engineering, alongside experienced engineers who value curiosity and learning.
  • Culture: Agile and startup-like, with quick decision-making and plenty of room to contribute ideas.
  • Balance: We believe in continuous feedback, lifelong learning, and supporting personal growth.

About Squirro

Squirro is the enterprise AI platform built for regulated industries, streamlining enterprise search and automating complex, custom workflows. Secure, private, scalable, permissions-aware, and fully auditable, the platform ensures that every result is accurate and verifiable. Squirro powers agentic AI applications that are grounded in the organization’s unique enterprise ontology.

Further information about AI-driven business insights can be found at:
https://squirro.com/

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