Senior AI, Knowledge Graph Engineer

🔥 16 minutes ago

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OrbisGraph by Pinnipedia

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

🔒 Cybersecurity

📋 Compliance

☁️ SaaS

Cybersecurity • Compliance • SaaS

OrbisGraph by Pinnipedia is a Germany-hosted compliance platform that models ISMS documentation as a versioned knowledge graph. It extracts assets, processes, requirements (e. g. , BSI IT‑Grundschutz, NIS2, DORA, KRITIS) measures, evidence and people from unstructured documents and generates tailored Sicherheitskonzepte (security concepts) for consultancies and in-house teams. Built by cryptography, AI and cybersecurity researchers and benchmarked/validated (Freie Universität Berlin), the product emphasizes explainable AI, source-linked human approval, sovereign German hosting (Deutsche Telekom Cloud), and readiness for the BSI’s Grundschutz++ machine-readable direction.

📋 Description

• Own the end-to-end pipeline that turns unstructured documents into a validated, queryable knowledge graph. • Accountable for extraction quality, graph integrity, and the data layer that backs the product's read path. • LLM extraction pipelines - document chunking, property and relationship extraction, cross-chunk reconciliation, gap detection. Built with structured-output LLM agents orchestrated by durable workflows. • Knowledge graph - schema design as typed Pydantic models, Cypher access patterns and indexing strategy, graph operations, schema evolution and migration. Scope ends at the graph boundary: API contracts and query abstractions exposed to consumers belong to the full-stack engineer. • Deterministic rule engines - table-driven evaluators for cases where code beats LLM judgment; clear contracts between deterministic and probabilistic components. • Data validation & quality - schema enforcement, required-property contracts, audit trails, eval harnesses (expert review, unsupervised checks, synthetic fixtures, LLM-as-judge). • Live data ops - backfills, coordinated migrations across relational + graph stores, observability on extraction throughput and quality, incident response.

🎯 Requirements

• 5+ years shipping data/AI systems to production with real customers - has been on-call for live pipelines and knows what breaks at 2am. • Strong Python (typed, modern) and SQL. • Comfortable with PostgreSQL under load. • Production experience with at least one graph database (Neo4j preferred; Neptune, ArangoDB, TigerGraph acceptable) - schema design, query tuning, not toy use. • Production LLM pipeline experience: structured output, agent orchestration, prompt and version management, evaluation frameworks. • Durable workflow orchestration in production (DBOS, Temporal, Airflow, Prefect, Dagster). • Test-first discipline - integration tests against real datastores (Testcontainers or equivalent), not mock-heavy unit tests. • Fluent English skills.

🏖️ Benefits

• Hybrid, full-time with flexible scheduling; occasional on-site days in Berlin. • Competitive salary: €60,000–€85,000 base (more for exceptional senior profiles). • Small, focused team; direct collaboration with the Product Owner and Full-Stack Engineer. • Modern tooling, real ownership, and a learning budget for role-relevant training. • Impact: help SMEs meet rising security requirements with less friction.