Spiral Scout is an AI-native international software development company where innovation meets high-performance engineering. Our team architects the future of digital ecosystems by combining deep-rooted expertise in custom web and mobile design with cutting-edge Generative AI.

We are seeking a Senior Python Engineer to join a client project for a live subscription product that turns public documents into structured records for research and reporting. The first assignment is a technical assessment of an inherited system. You will review the code and operating setup, find the gaps, and help define a focused release scope.

Engagement details: B2B contract, fully remote. The engagement starts with an initial technical assessment. Further implementation and ongoing support depend on the assessment results and will be agreed separately. Capacity (full time or part time) will be confirmed once the assessment plan is agreed.

Senior Python Engineering: 5+ years of commercial Python development, with proven ownership of production data or processing pipelines, not just contributing to them.
Technical Leadership: Experience independently leading a technical assessment or audit of an existing codebase and presenting findings and recommendations to stakeholders.
Cloud & Databases: Production experience with Google Cloud (Cloud Run or similar services) or an equivalent cloud, PostgreSQL, SQL data modeling, deployments and operations.
Data Quality at Scale: Hands-on experience designing validation, review and correction workflows, record lineage, and regression testing based on real error cases.
LLM-Based Extraction: Practical experience using LLMs to extract structured data from documents, including error analysis and combining model output with deterministic checks.
Language: Strong working English (B2 preferred) for client-facing technical discussions and written reports.

Nice to Have

Firestore, Streamlit or similar review tools
Next.js / TypeScript, enough to coordinate APIs and data contracts with the frontend
Experience improving a live SaaS or data product with strict data quality requirements

Mindset

Ownership of Inherited Systems: You can make progress with incomplete documentation and work safely around live data.
Direct Communication: You ask direct questions, report risks early and explain tradeoffs plainly.
Documentation Habit: You leave clear technical notes that others can use.

17 openings across locations