Head of Product

ExTrac is a decision intelligence company that provides services to governments and financial institutions. They are seeking a Head of Product to lead product management, develop product strategy, and ensure effective delivery of AI-driven products.

Responsibilities:

• Working closely with the CEO, develop, refine, and execute the product roadmap, aligning it with ExTrac's strategic objectives and client needs
• Translate the founders' vision for our AI-driven products into a product strategy you can defend: validate it, challenge it constructively, agree it with the founders, and then own its delivery, balancing user needs, business goals, BD requirements, and specific client requirements
• Support both long-term strategic planning and short-term sprint execution
• Stay across all product and engineering work in flight: who is working on what, expected timelines, and what is paused, delayed, or blocked
• Stay close to industry trends and competitor products, especially in AI and B2B SaaS
• Lead products end to end, from concept and planning through to delivery
• Translate visions, feature requests, and ideas into fully developed product briefs, leading discovery, pushing for clarity and further discussion where needed, and writing and maintaining clear, actionable PRDs
• Conduct investigations, gather information, and assess feasibility
• Keep all stakeholders aligned and up to date as plans and requirements evolve
• Apply technical judgement to guide product development, especially around AI/ML model integration, data processing, and analytics
• Translate complex technical solutions into clear, strategic product decisions
• Use behavioural data and analytics as a key input to decisions and prioritisation, alongside domain expertise and conviction
• Establish usage analytics and behavioural data to track adoption and surface friction, and build workflows to analyse and act on it
• Favour observation over interrogation: watching people work usually tells you more than asking them what they want
• Use user research and testing for what it does well, validating legibility, usability, and workflow fit. This evaluative feedback should carry real weight and is often decisive; workflow fit deserves particular care given our high-stakes users
• Recognise the limits of research when it comes to direction: what we should build is synthesised from deep expertise across intelligence analysis, subject matter, data science, engineering, and design
• For bets that cannot be validated up front, apply post-deployment discipline: define success metrics and evaluation timelines, commit in advance to the evidence that would change your mind, and assess honestly whether the bet is paying off
• Organise and run internal alpha and beta testing, plus external testing where possible; partner with Customer Success to recruit proxy users and to surface the friction, workflow issues, and pain points that feed into execution and prioritisation
• Partner closely with the AI team to ensure AI features are genuinely useful, understandable, and aligned with what our users need
• Help track and document the specific behaviours and styles built into Co-Analyst responses
• Support the work to adapt Co-Analyst to the needs of specific external organisations
• Build and formalise the product function: its agile processes, roadmapping systems, and prioritisation frameworks
• Bring order to the product operations layer: the tooling (issue tracking, documentation), delivery workflows, and the interface between product management and delivery management. Expect to roll up your sleeves here personally before you scale it
• Establish metrics to track product success, adoption, and customer satisfaction
• Grow and mentor a high-performing product team as ExTrac scales, fostering a culture of innovation and collaboration
• Act as the primary link between product, engineering, machine learning, design, customer success, and research, ensuring cohesive development cycles and smooth delivery
• Partner closely with the design team on design and UX, engineering on build and AI/ML, and the research and analysis team on domain expertise, synthesising their input into a coherent product direction
• Facilitate cross-team workshops to bring evidence and expertise together, and strengthen pre-sprint and in-sprint communication