Senior AI-BMad Engineer

## About the role Technical resource on the TME product team, partnering with a Project Manager. Builds and maintains data extraction and processing pipelines that transform EU tariff measures data (customs duties, tariffs, VAT, excise taxes) from government sources into structured, client-ready formats. Works using AI-assisted development tools and the BMAD methodology. This is a senior-level position requiring independent architecture and delivery decisions. ## Responsibilities - Develop AI native applications that extract and process trade compliance data from central EU and member state government sources — both structured (XML, JSON, CSV, HTML tables, APIs) and unstructured (PDF documents, legal text, prose regulations, scanned publications). - Design and built AI native data pipelines that monitor, detect changes, extract, normalise, validate, and release tariff measures data to clients. - Integrate AI/LLM capabilities into extraction workflows — using large language models for document understanding, entity extraction, classification, and data structuring. - Design and maintain data models for customs duties, VAT/excise information, and tariff measure metadata. - Ensure data quality through automated testing, benchmarking against official sources, data source and legal source comparison, and data validation pipelines. ## Required Technical Skills - 3+ years of professional software development - Proficiency in at least two programming languages — e.g., Python, JavaScript/TypeScript, Java, Go, C#, Rust, Kotlin, or similar. We value strong fundamentals over specific language experience - Methodology / Framework: Bmad Method - Strong knowledge is Retrieval-Augmented Generation (RAG, Model Context Protocol (MCP). - Data extraction and processing — web scraping, document parsing, API integration, ETL/ELT pipelines. Must be comfortable with both: Structured data: XML, JSON, CSV, HTML tables, databases, REST/SOAP APIs. Unstructured data: PDFs, legal text, prose regulations, HTML without clear structure, scanned documents. - Database design and querying — relational (PostgreSQL or similar) and/or document-based databases. Schema design, migrations, indexing. - API development — building and consuming RESTful APIs. - Version control — Git workflow, branching strategy, code review. - Automated testing — unit, integration, and data validation tests as part of development workflow. - Self-sufficiency – ability to analyse, design and build complete solution. - Rapid development – segment development into phasing to get results faster. - Influencer – demonstrate approach to other team members to lift group maturity. - Communication – can work with technical, business and project team members, participates in and leads discussion. ## Preferred Technical Skills - LLM/AI API integration (OpenAI, Anthropic Claude, Google Gemini) — for data processing, document understanding, or content extraction. - AI-assisted development tools (Claude Code, Cursor, GitHub Copilot, Windsurf, or similar). - NLP / document processing — OCR, text extraction, entity recognition, text classification. - Graph databases (Neo4j) or vector databases (pgvector). - Observability and monitoring (SigNoz, Grafana, Langfuse, or similar). - Containerisation and deployment (Docker, CI/CD pipelines).