Freelance Senior AI / Knowledge Graph Engineer (m/f/d) - REMOTE

Das ist der Job

We’re IGP-funded (2025/26) and co-develop with FU Berlin and pilot users from industry and security consulting.

Darum lohnt es sich

Requirements Must-have • 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. Benefits Remote, full-time with flexible scheduling. 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. Pinnipedia is a new Berlin startup building a cloud platform that automates and assists the creation of audit-ready IT-security concepts (e.g., BSI-Grundschutz, C5).

We’re looking for a freelance AI Engineer to turn messy inputs into structured knowledge and reliable answers. Your Mission -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.

Tasks • 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.

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.

PydanticAI, LangChain, DSPy, or Instructor all welcome. • 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. • Freelance status.

Nice-to-have • Experience with regulated, compliance-driven, or standards-heavy extraction domains (legal, medical, financial, security/audit). • Designed deterministic evaluators alongside LLM components and knows when to reach for which. • Contributions to data contracts, schema governance, or ontology work. • German language skills.

On a freelance basis. CET (Berlin) timezone availability expected. Possibility of relocation if successfull work relationship is achieved after a period of time. Competitive salary: 75.000–85.000 € base (premium for exceptional senior profiles). Impact: help SMEs meet rising security requirements with less friction.