Technical Product Manager at AI PropTech SaaS Start-up

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About the company

Our client is an early-stage AI PropTech SaaS business developing technology that helps property management teams automate time-consuming operational processes.

The platform uses AI to support areas including customer communications, compliance, maintenance coordination and scheduling, helping property businesses work more efficiently.

The business is entering an important stage of growth, with the product already being used by customers and the team continuing to develop its commercial offering.

The Role

We are looking for a Technical Product Manager to help build a product that customers can rely on.

Quality and product performance will be central to the role. You will take ownership of how the team evaluates product behaviour, including defining success criteria, developing test scenarios and monitoring performance over time.

Alongside this, you will support the day-to-day product operations of a fast-moving team. This will include triaging issues, working closely with Customer Success to turn customer feedback into clear priorities, and taking ownership of features through delivery.

The team makes extensive use of AI and automated workflows in its day-to-day operations. You should be comfortable working in an AI-enabled environment and interested in finding practical ways to use these tools effectively.

This is a broad role within a lean product and engineering team. You will contribute directly to roadmap and prioritisation decisions and will have the opportunity to develop further into AI evaluation, broader product ownership, or a combination of both.

You should be confident using AI tools in your daily work, have strong instincts for where AI-powered products can fail, and be interested in understanding how their performance can be evaluated and improved.

You will need enough technical knowledge to understand how the product works, discuss trade-offs with engineers and translate effectively between customer needs and technical possibilities, without needing to be a backend engineering specialist.

Key Responsibilities

Quality Assurance & AI Evaluation

• Own the quality standards for different areas of the product and define what good performance looks like.
• Build, maintain and improve evaluation suites and test scenarios across different product workflows.
• Develop and refine the criteria used to assess AI-generated outcomes.
• Monitor product performance against evaluations over time, identify regressions and help drive improvements.
• Use real customer interactions to identify new test scenarios and ensure evaluation remains grounded in how the product is actually used.
• Work closely with engineering and AI colleagues to turn evaluation findings into practical product improvements.

Issue Triage & Product Operations

• Review and triage product issues identified through customer interactions and internal monitoring.
• Determine whether issues relate to configuration, data, user behaviour or genuine product defects.
• Provide engineering teams with the context needed to investigate and resolve issues efficiently.
• Help maintain a clear and current view of product priorities, work in progress and blockers using tools such as Linear and Notion.
• Support effective product operations across a fast-moving technical team.

Customer Success & Feedback Loop

• Analyse customer feedback, conversations and other feedback channels to identify recurring themes and product problems.
• Work closely with Customer Success to translate customer needs into clearly defined product priorities and tickets.
• Bring customer feedback, quality data and product performance insights into regular product and technology prioritisation discussions.
• Communicate product updates and new functionality clearly to internal teams and customers.

Product Ownership & Roadmap

• Own features through the product lifecycle, from problem definition through delivery and validation.
• Write clear product requirements, success criteria and supporting documentation.
• Work closely with engineering to ensure requirements are understood and achievable.
• Contribute directly to roadmap and prioritisation decisions.
• Support the development and launch of new product capabilities as the platform grows.

Requirements

Must Have

• Around 3-5 years of experience in a product role, or a closely related role where you owned outcomes and worked directly with engineering teams.
• Strong practical experience using AI tools as part of your day-to-day work.
• Comfortable operating in a team that uses AI and automated workflows extensively.
• Hands-on technical grounding, either through previous software development experience or through building AI-powered or automated workflows yourself.
• Enough technical understanding to discuss feasibility and trade-offs confidently with engineers.
• Strong instincts for product quality and a structured approach to measuring performance.
• Excellent written and verbal communication skills, with the ability to explain technical subjects clearly to different audiences.
• A methodical, root-cause approach to diagnosing issues.
• Comfortable using data, dashboards and operational tools to understand product performance.
• Strong interpersonal skills and confidence working with both customers and technical teams.
• High ownership and follow-through, with the ability to work effectively in a fast-moving early-stage environment.
• Comfortable being open about what is and is not working and helping the team improve accordingly.

Strongly Preferred

• Experience with AI evaluations, model testing, prompt evaluation, or creating and refining test scenarios for AI systems.
• Experience owning quality assurance or product quality standards.
• Familiarity with tools such as Linear, Notion and Slack.
• Experience working with AI-powered products and setting realistic expectations around their behaviour.

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