Principal Engineer

About the role

You will own the most complex technical challenges that span across the entire 9fin platform, ensuring coherence where no single team can claim clear ownership. This role requires you to step into the hardest problems at the intersection of AI, analytics, and data infrastructure, where the stakes for failure are exceptionally high. You will define and enforce the architectural standards that allow our diverse product and engineering teams to move quickly without compromising reliability or scalability. Your work will directly shape how financial entities and relationships are modeled, resolved, and surfaced across all downstream systems. You will act as the senior technical conscience for the organization, making final decisions that balance long-term integrity with urgent business needs. This is a hands-on leadership position where you must remain deeply connected to the code while influencing the direction of multiple disciplines. You will be the definitive voice on how foundational systems are designed, built, and maintained across the company.

Key facts

What you'll do

Define and maintain the core data model and entity resolution strategy that underpins how issuers, instruments, deals, counterparties, and legal documents are represented across 9fin.

Own the foundational architectural decisions that impact multiple teams and are difficult to reverse, requiring careful analysis, RFC authorship, and cross-team facilitation.

Provide architectural coherence to major initiatives within Analytics, AI, Platform, and Product Engineering, aligning them with the long-term vision for the platform.

Identify and mitigate technical risks and compounding complexity before they escalate into critical incidents affecting data integrity or system reliability.

Set and uphold rigorous standards for engineering quality, including system design, observability, reliability, and API contract design across all product areas.

Write code that proves critical design hypotheses, validates complex data transformations, and establishes patterns that other engineers can reliably follow and extend.

Mentor and stretch the most senior engineers across the organization, elevating their ability to think and execute at the level required for a global debt markets platform.

Be the primary technical voice in cross-team planning, roadmap discussions, and build versus buy analyses, ensuring that tradeoffs are explicit and well understood.

Ensure that foundational systems are observable, debuggable, and maintainable at scale, enabling fast and safe iteration across data, AI, and product workflows.

Champion best practices in data modeling, pipeline robustness, and system scalability, creating a baseline that new initiatives must adhere to from the start.

Balance pragmatic delivery with architectural integrity, making decisions that serve immediate needs without compromising the future evolution of the platform.

Drive the evaluation and adoption of new technologies and patterns where they meaningfully improve the reliability, performance, or clarity of our core data and AI systems.

Requirements

You have operated at a principal or staff level in fast-moving, data-intensive engineering organizations and can demonstrate a consistent track record of ownership and impact across multiple domains.

You can credibly engage in deep technical discussions about data pipeline architecture, RAG evaluation, API design, and system scalability, adding substantive insight across multiple disciplines.

You own problems end to end, making final decisions and accepting accountability for outcomes rather than only offering opinions or recommendations to others.

You write code when it matters, producing proof-of-concept implementations, deep technical investigations, and foundational code that sets long-term examples for the rest of the engineering organization.

You hold strong, well-reasoned opinions about engineering practices and can defend them rigorously while remaining open to being wrong when presented with better evidence.

You are energized by complex, poorly defined problems that span multiple systems and teams, and you remain focused under pressure when ambiguity is high.

You have deep, hands-on experience with complex data modeling, entity resolution, and production-grade data pipelines where correctness and performance are non-negotiable.

You have designed and shipped AI or LLM-based systems beyond the prototype stage, including RAG pipelines, structured extraction patterns, and evaluation frameworks that meaningfully impact production behavior.

You possess strong backend and distributed systems expertise, including API design, service architecture, scalability strategies, and robust observability practices.

You have a history of making and owning foundational architectural decisions that reshaped how an entire engineering organization operates and delivers value.

You are highly proficient in Python and can comfortably learn and apply adjacent technologies where they meaningfully support your work.

You have a demonstrated understanding of the unique constraints and realities of financial data, including issues of timeliness, lineage, provenance, and regulatory context.

You are comfortable working with semi-structured and evolving data representations, including legal documents, entity hierarchies, and complex contractual instruments.

You have operated in environments where system reliability, auditability, and clear communication with both technical and non-technical stakeholders are essential.

You are open to mentorship and to elevating the technical bar for senior engineers, helping them grow into the level of ownership this role demands.

Nice to have

Prior experience with financial data, legal documents, or other domain-rich, semi-structured datasets that require careful modeling and reconciliation.

A background as a founding engineer, early-stage CTO, or technical lead who has built systems from scratch and carried the responsibility for their long-term consequences.

Practical notes

This role is full-time and based in London.