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Senior product manager, commerce - ai & platform (100% remote - ireland)

Stromness
Hopper
Product manager
€60,000 a year
Posted: 4h ago
Offer description

Employer Industry: Travel Technology


Why consider this job opportunity:

* Opportunity to work with a well-funded startup in the travel technology sector, with competitive salary and potential pre‑IPO equity packages.
* Flexdesk All Access Pass & Work‑from‑home stipend, promoting a flexible work environment.
* Entrepreneurial culture encouraging innovation and taking risks.
* Open communication with management and leadership, fostering a collaborative atmosphere.
* Chance to make a significant impact in a small, dynamic team.


What to Expect (Job Responsibilities):

* Own architecture decisions for authentication, APIs, loyalty, and payment systems.
* Ship features that significantly reduce partner integration time.
* Build products for both internal teams and external B2B partners, balancing priorities.
* Collaborate with senior engineers to develop a prioritized roadmap for AI/ML capabilities.
* Manage the entire product lifecycle, from opportunity identification to MVP definition, shipping, and iteration.


What is Required (Qualifications):

* Minimum of 5 years of experience in product management, with at least 2 years in B2B or platform products.
* Proven experience designing APIs and SDKs, with a strong understanding of their adoption and maintenance.
* Familiarity with SQL, A/B testing, and data‑driven product decision‑making.
* Experience building and launching products from scratch, particularly in the B2B or platform space.
* Ability to communicate effectively, document clearly, and facilitate cross‑team decisions.


How to Stand Out (Preferred Qualifications):

* Experience working with AI APIs (e.g., OpenAI, Anthropic) or implementing AI features.
* Background in discussing technical trade‑offs and prioritizing shipping over perfect architecture.
* Regular engagement with customers to gather feedback for product prioritization.
* Ability to stay effective in a fast‑paced environment with shifting priorities.
* Knowledge of LLM limitations and when to use RAG versus fine‑tuning.
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