Product Owner

EcoOnline

1d•Hybrid

About The Position

As our Product Owner you will play a key role in delivering safety-critical software used by emergency services, government agencies, corporate resilience and business continuity teams when it matters most. Sitting within our Product Operations team, you will own day-to-day product delivery for D4H, translating approved roadmap initiatives into high-quality, measurable and supportable software deliverables. You will work closely with Product Management, Engineering, Architecture, QA and operational stakeholders to ensure teams have the clarity, direction and product decisions needed to deliver effectively. This is an opportunity to help evolve a trusted, proven platform as it scales into new markets and connects into EcoOnline’s broader EcoOne platform, including identity, data and analytics, and dedicated AI platform services. You will play a key role in helping EcoOnline move customers from compliance to visibility to prediction, with AI becoming a first-class capability that supports crisis readiness, incident response and operational resilience.

Requirements

2+ years’ experience as a Product Owner or Product Manager delivering software products.
Fluent, practical and daily use of AI tools to write specs, groom backlogs, analyse information and move faster.
Demonstrated technical fluency, with the ability to work confidently with Engineering and Architecture teams.
Experience influencing without authority and driving decisions across multiple R&D teams or stakeholder groups.
Experience shipping AI-built or AI-designed product features, with an understanding of what makes an AI capability production-ready, trustworthy and usable in high-stakes environments.
Strong backlog and delivery management skills across epics, stories, acceptance criteria and the software development lifecycle.
Comfortable working with technical concepts such as APIs, data models and system architecture.
Strong stakeholder management skills, with the ability to balance competing priorities across internal teams.
Working knowledge of AI and LLM concepts, such as prompting, RAG, model limitations and evaluation.
Awareness of AI governance, data sensitivity and compliance considerations in regulated, multi-region product environments.
Curiosity, pace and commercial awareness, with the ability to understand the “why” behind product decisions and keep delivery moving.

Nice To Haves

Ideally, experience in public safety, emergency management, crisis or business continuity, or other safety-critical or mission-critical software environments.

Responsibilities

Translate roadmap initiatives into deliverable product solutions, increments, epics, features and user stories.
Own backlog quality and prioritisation, ensuring engineering teams have clear, actionable and well-defined requirements.
Use AI day-to-day to accelerate specification writing, backlog grooming, data analysis and QA acceptance.
Work closely with Product Management and Engineering to shape solutions that balance customer needs, technical constraints and delivery timelines.
Manage delivery scope while protecting agreed objectives, escalating significant changes where strategic decisions are required.
Provide timely product direction throughout delivery, resolving day-to-day questions around execution, operations and implementation.
Coordinate release readiness, including documentation, release notes, operational preparation and successful deployment.
Define clear acceptance criteria, support testing and quality assurance, and ensure delivered capabilities can be measured after release.
Use customer feedback and product data to support continuous improvement and maintain high product quality.
Factor AI governance, data-handling considerations and model limitations into product design, acceptance criteria and delivery decisions.