AI Product Manager & Squad Lead — Built for B2B SaaS

Referment; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Referment is working with a London-based company that has built an AI platform turning data from major construction projects into decisions their leaders can act on — forecasting delay and cost risk on large infrastructure and helping the people running those projects decide what to do about it. The underlying ML capability is trained on one of the largest datasets of construction schedules.

The company runs product differently from most.

Qualifications

• 2+ years owning a B2B or enterprise AI or SaaS product with shipped features.
• Experience building with AI daily, prototypes, analysis, and working code you review and edit.
• You've built with LLMs, including prompting, context, retrieval and tool use.
• You can derive customer needs and make trade-offs under uncertainty.

Responsibilities

• Own your squad's quarter: plan it, reconcile with unplanned work, and deliver evidenced decisions.
• Write clear specs, prompt agents, and review/edit generated code and output.
• Design and ship AI agents, defining their behaviour and guardrails.
• Run structured evaluations with datasets and scoring rubrics.
• Help people decide under uncertainty, turning forecasts into actionable insights.
• Get close to customers through user and buyer research and client meetings.
• Lead contributors across squads, coordinating dependencies.

Skills

B2B SaaS product ownership

AI product development

Prototyping with AI tools

LLM prompting and tooling

Data-driven decision making

Cross-functional leadership

Structured evaluations

Strong communication

Job description

Referment is working with a London-based company that has built an AI platform turning data from major construction projects into decisions their leaders can act on — forecasting delay and cost risk on large infrastructure and helping the people running those projects decide what to do about it. The underlying ML capability is trained on one of the largest datasets of construction schedules.

The company runs product differently from most.