About 9fin

9fin is the AI platform powering global debt markets — the world’s largest asset class at over $145 trillion.

Debt markets are vast, global, and mission-critical, yet still run on fragmented data, PDFs, and manual workflows. 9fin replaces this broken infrastructure with a single platform that centralises proprietary credit data, deep analysis, and high-value workflows across global markets.

Today, 9fin powers teams at 300+ blue-chip institutions worldwide, including global banks, asset managers, private equity firms, law firms, and advisors. The business is scaling at exceptional speed, with rapid expansion in the US and best-in-class retention driven by deep workflow adoption.

We’re at a defining inflection point. With proven product-market fit and strong, global market pull, 9fin is accelerating toward becoming the category-defining platform for debt markets worldwide.

The Opportunity

Debt is a $145 trillion market that still runs on PDFs and spreadsheets. 9fin is changing that: AI-powered intelligence that gives 300+ banks, asset managers, PE firms and law firms the answer in minutes, not days. We’ve just closed our Series C, and AI is at the heart of what we build next.

We’re looking for a Senior AI Platform Engineer to build the foundation beneath it. This is greenfield: a V1 exists, but the big decisions are still ahead. You’ll design the core platform behind Generative AI, Agentic AI and ML at 9fin: one home for every agent, delivering “AI as a service” to a dozen or more teams.

Your work will power everything from document understanding to autonomous agents that run scheduled workflows, write morning briefings and flag distressed companies.

What You’ll Work On

No two weeks look the same, but you can expect to:

Build the platform behind our agents: agent runtime and orchestration, model serving, sandboxing, and tracing and evals

Create shared components: prompt management, AI gateways and evaluation services

Ship APIs, SDKs and tooling so teams can launch agents without rebuilding infrastructure

Design secure, scalable deployment pipelines for models and applications

Build observability: tracing, evaluation, cost and quality in production

Set standards for testing, governance, Responsible AI and operations, and keep evolving the platform as the ecosystem moves

What Makes This Role Different

Build, don’t maintain. Many architectural decisions are still open, and they’re yours to shape.

A real roadmap. Memory, artifacts and event-driven agents come first. Within six months, you’ll help ship agents that run autonomously in the background.

A top 2027 bet. Agent orchestration is a strategic priority, and you’ll help drive it, towards a 9fin experienced through agents.

Leverage. You’ll build shared capabilities that let multiple teams ship AI at scale, rather than owning a single product.

Real influence. You’ll be one of a small group of senior engineers shaping direction alongside the Engineering Lead. No management duties required.

About You

You’ll be a great fit if you are an engineer who has built real AI systems in production, cares about developer experience, and wants to own something from the ground up.

AI Platform Engineering

5+ years of software engineering experience, including 2+ years building AI/ML platforms, Generative AI applications or production machine learning systems

Experience designing and deploying enterprise AI applications to production, with a focus on scalability, reliability and developer experience

LLMs & Agentic AI

Hands-on experience building applications powered by Large Language Models

Experience building Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG) solutions, using embeddings, vector databases and modern LLM orchestration frameworks

Experience building or contributing to agentic AI systems, intelligent workflows or orchestration frameworks

Backend & Platform Engineering

Strong backend engineering with production experience in Python and/or TypeScript

Experience designing scalable backend services and REST APIsExperience building reusable platform capabilities, internal developer tooling, SDKs or shared engineering services