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.
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/
Squirro New York, New York, USA Office
33 Irving Pl, New York, NY, United States, 10003
Similar Jobs
Machine Learning • Payments • Security • Software • Financial Services
Design, develop, test, deploy, maintain, and debug software solutions. Create technical designs and documentation, propose solutions for complex business needs, and support release and integration activities while following SDLC and risk management practices.
Machine Learning • Payments • Security • Software • Financial Services
Lead and mature detection and incident response lifecycle, run day-to-day SOC operations, manage on‑call readiness, drive SIEM detections and automation, coordinate cross‑team responses, maintain playbooks and run readiness exercises, mentor analysts, and ensure regulatory and post‑incident improvements.
Top Skills:
Cloud SecurityEdrElasticEndpoint SecurityFedrampHipaaIdentity And Access ManagementIds/IpsIso 27035JIRAMitre Att&CkNist 800-61Pci DssServicenowSIEMSoc 2SplunkThreat Intelligence
Big Data • Information Technology • Software • Analytics • Energy
Lead enterprise SaaS sales for financial services within the energy sector. Build C-suite relationships, drive pipeline generation (3.5x quota), manage sales pursuits and teams, develop tailored presentations and business cases, execute consultative selling, maintain CRM and sales data, and achieve retention, upsell, and revenue targets.
Top Skills:
Microsoft AccessExcelMicrosoft OutlookMicrosoft PowerpointMicrosoft WordOwner Relations SoftwareSalesforce
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
