Senior Forward-Deployed Software Engineer Needed to Finish Enterprise Intelligence Platform MVP (Python / FastAPI / Graph / Data Pipelines) ⸻ Project Overview I am building RealScore, a financial intelligence infrastructure platform designed for investigators, regulators, financial institutions, and government entities. The system ingests public records and financial intelligence data, resolves entities, constructs ownership relationships, and produces explainable risk outputs. The repository is already substantially built. The core architecture, services, pipelines, and UI are implemented and functional. The first core feature (entity search → ownership → sanctions exposure → explainable risk scoring) is approximately 70–80% complete. However, it needs a high-level engineer to finish the final mile and bring the feature to production-quality MVP pilot readiness. This is not a greenfield project and not a beginner task. You will be working with an existing codebase containing: • Data ingestion pipelines • Entity resolution logic • Risk scoring • Graph relationships • Search APIs • Frontend investigator interface I need someone capable of reading the repository, understanding the architecture quickly, and finishing the system without heavy supervision. ⸻ Current Architecture Backend Python 3.11 FastAPI SQLAlchemy Pydantic Data Systems PostgreSQL Neo4j (graph relationships) Frontend Next.js 15 React 19 TypeScript TailwindCSS Infrastructure Docker Alembic migrations Prometheus / Grafana monitoring Services in Repository Current services include: • API gateway • data ingestion services • normalization services • entity resolution service • graph service • risk scoring service • alert engine • search service • evidence / integrity services The system currently exposes ~23 API endpoints and includes a working UI. ⸻ What Is Already Working The system currently performs the following flow: Data ingestion → normalization → integrity seal → entity resolution → graph upsert → risk scoring → alert generation. The frontend already includes: • dashboard • entity search • entity details • relationship graph • alerts • evidence export The feature works but needs performance improvements, reliability fixes, and result quality improvements. ⸻ What Needs to Be Done Your responsibility is to finish the first feature to production-quality MVP readiness. This includes: 1. Search Performance and Relevance Improve entity search responsiveness and ranking. Search should: • return results instantly • prioritize relevant entities • handle partial queries • support real-world datasets 2. Entity Resolution Improvements Improve entity matching logic so results are: • accurate • deduplicated • consistently linked across data sources 3. Data Pipeline Stability Audit the ingestion and pipeline services to ensure: • idempotent ingestion • consistent normalization • reliable processing 4. Result Completeness Ensure returned entity profiles include all available information such as: • ownership relationships • sanctions exposure • risk scoring • related entities 5. Backend Optimization Optimize API endpoints and database queries to reduce latency. 6. Graph Integration Improve graph relationships and traversal for ownership and related entities. 7. Frontend Integration Ensure the frontend displays all relevant entity data clearly and correctly. 8. Evidence Traceability Outputs must clearly show why the system generated a given risk score. Explainability is important. ⸻ This Role Is NOT For Please do not apply if you are: • a junior developer • someone who only builds CRUD apps • someone who needs step-by-step direction • someone who has never worked with large codebases • someone unfamiliar with data pipelines • someone unfamiliar with backend architecture This project requires someone who can operate independently and make strong engineering decisions. ⸻ Ideal Candidate You should have experience with: • large Python backend systems • FastAPI or similar frameworks • data pipeline architecture • entity resolution or identity matching • graph databases (Neo4j preferred) • PostgreSQL performance optimization • search systems • containerized infrastructure Experience building systems used by investigators, financial systems, compliance tools, or data platforms is highly valuable. ⸻ The Kind of Engineer I’m Looking For Someone who: • reads the codebase and understands the system quickly • identifies weaknesses without needing instructions • proposes improvements proactively • writes clean production-quality code • cares about performance and reliability • can finish complex systems without babysitting Think forward-deployed engineer or founding engineer mindset. ⸻ Deliverables The goal is a fully stable first feature ready for pilot deployment. Success criteria include: • fast entity search • accurate results • complete entity profiles • stable pipelines • clean frontend display • explainable risk scoring ⸻ Timeline I am looking for someone who can move quickly once they understand the system. Initial engagement will focus on finishing this feature. If the work is excellent, there is opportunity for long-term involvement on the platform. ⸻ To Apply Please include: 1. Links to complex backend systems you have built 2. Experience with Python / FastAPI / data pipelines 3. Experience working on large production systems 4. A short explanation of how you would approach improving search performance in a system like this Applications that do not demonstrate serious engineering experience will not be considered. ⸻ Final Note This is not a typical freelancer project. The platform is intended to become enterprise-grade intelligence infrastructure. I am looking for someone capable of operating at that level. ⸻ If you are a high-level engineer who enjoys solving complex system problems, I would like to work with you.