Top Tech Jobs & Startup Jobs in London

Owns the organization’s most complex cross-team engineering problems, including financial data modeling, entity resolution, AI/LLM systems, distributed architecture, scalability, reliability, and observability. The Principal Engineer makes foundational architectural decisions, writes RFCs and production code, establishes engineering standards, identifies technical risks, and mentors senior engineers across Analytics, AI, Platform, and Product Engineering.

Develop high-yield bond covenant research and analytics by reviewing and analyzing bond documentation, writing market and thematic reports, answering client questions, expanding covenant databases, and collaborating with engineering and product teams. The role also involves delivering seminars and representing 9fin at industry events and in the press.

Own the 0-to-1 strategy and execution for 9fin’s external data products, including APIs, data shares, and future cloud delivery mechanisms. Define data packaging, schemas, developer experience, pricing, entitlements, SLAs, and compliance policies. Partner with engineering, analytics, domain teams, Sales, Legal, and enterprise clients to validate products through pilots and launch a solution-selling, usage-based commercial model.

Lead technical vision and architecture for the Core Markets engineering organization. Design scalable backend systems, APIs, and shared platform capabilities; guide architecture across multiple teams; lead cross-team initiatives; and improve reliability, scalability, observability, and developer experience. Partner with AI and Retrieval teams on search and RAG systems, contribute to critical code paths, mentor engineers, and influence technical direction without direct authority.

Design and build generative AI applications for complex financial and legal workflows. Lead the full model lifecycle from experimentation and training through testing, monitoring, and deployment. Apply advanced techniques across information retrieval, knowledge graphs, recommendation systems, statistical modeling, and GenAI. Collaborate cross-functionally, translate business problems into scoped initiatives, mentor teammates, promote AI adoption, and deliver production-ready solutions with strong product impact.

Backend Engineer responsible for designing systems, developing Python backend services, APIs, data processing, automation, and web application functionality. The role includes technical leadership on projects, code reviews, mentoring, experimentation, refactoring, documentation, and collaboration with product, financial, legal, and editorial teams. The engineer will work primarily with Flask, FastAPI, PostgreSQL, AWS, Lambda, Docker, and ECS.

Build production generative AI systems for complex financial and legal workflows. Responsibilities include document understanding, structured information extraction, model lifecycle management, retrieval and context engineering, data validation, evaluation, deployment, and monitoring. The role requires collaboration across teams, mentoring, product focus, and applying advanced AI research to convert legal and financial documents into reliable structured data.

Lead cross-functional engineering projects from system design through deployment, building backend services, APIs, data processing, automation, and web application functionality. Work across Python, TypeScript, React, AWS, and PostgreSQL while mentoring developers, conducting code reviews, improving developer experience, and collaborating with product, design, clients, and domain experts. Own features through iteration and contribute to AI-enabled financial data and workflow products.

Design and build generative AI applications for complex financial and legal workflows. Lead the end-to-end model lifecycle, including experimentation, training, evaluation, monitoring, and deployment. Apply machine learning, information retrieval, knowledge graphs, recommendation systems, and agentic AI techniques. Collaborate across teams, translate business problems into experiments, promote AI adoption, and mentor teammates while delivering scalable, production-ready systems on AWS.

Owns content analytics end to end, including engagement measurement, event instrumentation, audience analysis, content classification, competitive coverage tracking, and editorial attribution. Builds dbt models in BigQuery or similar warehouses and maintains the Omni semantic layer for trusted self-service reporting. Partners with editors to diagnose performance drivers, prioritize coverage, and translate complex analysis into actionable editorial strategy.