9fin
Senior AI Product Manager
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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
Our AI product area is growing. We already have two Product Managers working across conversational AI, agentic workflows, and domain-specific automation, and we need a third to expand our capacity as the scope of AI at 9fin accelerates.
Backed by over $170M in funding (Series C), we are scaling rapidly across product, engineering, and go-to-market. AI is not a bolt-on feature at 9fin; it is the core differentiator for the next phase of the company.
You will join an established AI PM team and take ownership of a product area within our AI surface. This could span new AI-powered features for credit analysts, workflow automation for legal and financial analysis, or expanding our conversational AI into new domains. The team has already built evaluation infrastructure and quality frameworks; you will use and contribute to these rather than build them from scratch.
You will work within our product organization (eight squads across AI, data, and domain verticals) and partner closely with ML engineers, data scientists, domain experts, and designers. This is a high-autonomy role with real scope to shape what 9fin's AI products can do for our clients.
What You'll Do
Product Strategy & Execution
- Collaboratively create and champion a clear product vision and strategy for your area, with a focus on building and evolving our AI products
- Synthesize qualitative and quantitative insights into problem statements that identify root causes, not just symptoms
- Shape the next generation of agentic AI products: multi-step reasoning workflows, tool orchestration, and autonomous task completion for financial professionals
- Demonstrate a working understanding of the challenges specific to building with LLMs, including managing hallucinations, evaluating output quality, and designing for non-deterministic systems
- Use confidence-building methods (prototypes, user research, data analysis) to understand how users will interact with AI-powered products before committing to full builds
AI Quality & Data
- Use the team's AI evaluation framework (LLM-as-judge protocols, quality thresholds, SME eval cycles) to validate and improve the products you ship
- Contribute to the data strategy for your product area: annotation quality, ground truth curation, and feedback loops that improve model performance over time
- Proactively identify and track metrics that measure client and business benefit, working with the team on continuous model evaluation and improvement
Team Leadership & Communication
- Create a collaborative environment for your squad, providing wider context and clear goals so everyone can do their best work
- Work with data scientists and ML engineers to bridge the gap between business needs and the technical capabilities of AI models
- Communicate strategy, initiatives, and progress transparently across the organisation
- Translate complex AI concepts, capabilities, and limitations into language that non-technical stakeholders can act on
- Champion responsible AI practices: transparency in model outputs, bias monitoring, and compliance with client expectations around AI-generated content
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What We're Looking For
- 5+ years of product management experience, preferably in FinTech or B2B SaaS, with at least 2 years focused on ML or GenAI products
- Working knowledge of RAG architectures, embeddings, prompt engineering, and LLM evaluation methods (not just "AI concepts" at a high level)
- Experience shipping AI products where output quality is probabilistic: you know how to define "good enough" and iterate from there
- Comfortable reading Python notebooks and SQL to interrogate model outputs and usage data
- Track record of shipping AI products where you managed the tension between ML research/exploration and production delivery constraints
- Collaborative leadership style with strong stakeholder management; you build relationships that empower your team to achieve outcomes
- User-centric communication skills: you can explain AI capabilities and limitations to clients and internal stakeholders without overselling or underselling
- You thrive in fast-paced, ambiguous environments and are energised by the challenge of building something new
Nice to Have
- Experience in financial services, legal tech, or data/analytics platforms
- Familiarity with credit markets, debt instruments, or regulatory/compliance workflows
- Experience with NLP applied to document analysis (contracts, legal filings, financial reports)
- Experience with agent orchestration frameworks, tool use patterns, or multi-step AI workflows
The Opportunity
9fin is already the leading platform for legal intelligence in debt capital markets. Our proprietary AI capabilities extract and analyse legal language at scale, and our unique dataset of credit legal documentation delivers intelligence that generic AI tools simply cannot match.
Now we are investing to extend that leadership. You will lead a dedicated engineering team to define the next chapter of 9fin's legal product — going deeper on AI, building richer workflows, and expanding into the law firm segment, where we see a significant TAM opportunity that is ours to capture.
Your users sit at the centre of the debt markets ecosystem: origination teams at top investment banks, lawyers at leading law firms, and credit analysts at hedge funds and credit funds.
This is a great opportunity to shape the future of a product and a company that's using technology to revolutionise the trillion-dollar debt capital market.
Key Responsibilities
Product Strategy & Execution
- Strategy: Define and champion the product vision and strategy for the Covenants squad from the ground up, working closely with engineering, our legal analysts, and key customers to establish what to build and why.
- Problem definition & structured thinking: Synthesise insights from in-house legal subject matter experts (SMEs), customer interviews, customer feedback and data signals to craft a clear problem statement, articulating the root cause in a structured way.
- Discovery: Use a range of techniques to identify and understand what users need and their workflows, across a sophisticated professional audience spanning credit analysts, portfolio managers, restructuring advisors, and law firms.
- Impact driven: Align the team around a key outcome and effectively prioritise initiatives across multiple dimensions.
- Measuring success: Proactively identify and track metrics to measure client and business benefit. Work with the team to define and manage a process for continuous model evaluation and improvement, with particular attention to the accuracy and reliability standards required in legal contexts.
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Team Leadership & Communication
- Team success: Create a collaborative environment for your squad, providing wider context and clear goals so everyone can do their best work.
- Communication: Ensure all people involved are aware of the team's strategy, initiatives, and progress. You must be able to effectively communicate complex legal and financial concepts to technical audiences, and similarly communicate technical capabilities to legal and credit professionals.
- Influence: Build strong relationships to empower the squad to achieve the desired outcome, often by influencing stakeholders outside of your team.
- Stakeholder management: Work closely with stakeholders, including 9fin's legal analysts, credit team to gather the right input and insights. You will need to listen carefully and bring people on a journey.
AI Product Development
- Own the roadmap for AI-powered legal document extraction and covenant analysis, ensuring outputs meet the precision standards required for professional use.
- Partner with software and AI engineering to define evaluation frameworks for AI outputs in legal contexts, where accuracy, source attribution, and explainability are critical to user trust.
- Identify opportunities to apply emerging AI capabilities to novel legal workflow problems, from covenant compliance monitoring to cross-document analysis across deal histories.
About You
This role will be a great fit if:
- You have a legal or financial markets background, or have built products for this audience. You may have started your career as a lawyer, paralegal, or credit analyst, or you may have been a PM at a legal tech company. You are able to hold a substantive conversation about credit agreements, covenant packages, and how legal language governs capital structures. A sharp PM from an adjacent domain who can demonstrate rapid domain immersion will also be considered.
- You are a strategic thinker who thrives with a blank page. You are comfortable defining strategy from scratch, not just executing an existing roadmap. You can synthesise ambiguous inputs into a clear direction and bring a team with you.
- You're a collaborative leader. You have an empathetic leadership style and build strong, effective relationships. You love working autonomously but are able to earn the trust of others with a collaborative style. You are great at prioritising, not afraid to say no, and excel at managing stakeholders while also being confident in voicing your own opinions and challenging others.
- You've got hands-on experience with AI. You have experience with or a working knowledge of AI and LLMs, including how to evaluate model outputs in production environments. You understand what good looks like when AI is applied to high-stakes, precision-dependent workflows, and you can engage meaningfully with engineering teams on evaluation design and quality standards.
- You work in an AI-native way. You use generative
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