The Opportunity

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 organization.
• 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.

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 energized 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.

Benefits

• Competitive, market-benchmarked salary.
• Pension with 7% company matching.
• Private medical insurance, paid sick leave, income protection, group life assurance.
• Season ticket and cycle-to-work schemes.
• Hybrid flexibility with up to 3 months annual work abroad.
• 25 holiday days plus local public holidays (exchangeable).
• One-month paid sabbatical after 5 years; enhanced parental leave.
• Professional development budget and regular social events.