Product Manager - Storefront
At Salla, we are building the digital backbone of commerce in the region, empowering thousands of merchants to start, grow, and scale their businesses. We turn what's complex into something simple, powerful, and scalable.
Every Salla store runs on one storefront. When a buyer searches, opens a product, or reads a review, they decide whether to trust a store they may have never heard of. Every change you ship reaches thousands of stores at once.
We are looking for a Product Manager who builds with curiosity, clarity, and care. You own search, the product page, and reviews: how buyers find what they want, decide, and trust what they read. You work side by side with our data and AI teams and turn their models into decisions buyers feel and merchants see in their sales.
Core Responsibilities:
- Know Salla's buyers: how they shop across very different stores, and what makes them hesitate, compare, or leave. Bring their voice into every decision, along with the merchants whose sales depend on it.
- Own search, the product page, and reviews end to end, from discovery to iteration, tied to buyer conversion and merchant sales.
- Partner with data and AI teams on ranking, query understanding, and semantic search. Decide what ships, to which stores, and how you measure it.
- Design the product page around the buyer's decision: what they need to see, trust, and confirm before they buy.
- Build reviews that buyers trust and merchants can use, including for stores with few or no reviews.
- Experiment by default and Ship safely across thousands of stores: staged rollouts, experiments, guardrails, and a way back.
- Run continuous discovery: talk to buyers and merchants regularly, watch real sessions, and test ideas with prototypes before committing engineering time.
- Make decisions with data: define the metrics that matter for each surface, read the funnel yourself, and let evidence, not opinion, settle debates.
Requirements
- 4–6 years of experience in Product Management, preferably owning Search, Discovery, Product Pages, Conversion, or other customer-facing product experiences within a live consumer or e-commerce product.
- Proven experience driving product metrics and business outcomes, with the ability to explain what changed, why it changed, and how the impact was measured.
- AI-native mindset with hands-on experience using AI tools for data analysis, prototyping, research and interpreting product results.
- Experience working closely with Data Science and Machine Learning teams on Search, Ranking, or Recommendation with a clear understanding of product ownership and decision-making responsibilities.
- Hands-on experience conducting User Research and Product Experiments, using insights to influence product decisions.
- Strong understanding of Arabic Search and Discovery, including Arabic spelling variations, dialects, transliteration, Arabic-English mixed queries, and search behavior.
- Demonstrated ownership of product outcomes, with the ability to work independently, take initiative, and move quickly in a fast-paced environment.
- You simplify: you cut before you add.
- Fluent in Arabic and English, both written and spoken.
- Preferred: Experience building a product, feature, or business from 0-to-1, either as a founder, early-stage team member, or founding product team member.
Skills
As published by workable · 6 questions · 4 written answers
Basics
First name, Last name, Email, Phone, Address, Nationality, Iqama Status, Current Salary, Resume, Summary, Experience, Education
Short answers (2)
- Do you have relatives in Salla? If Yes, please clarify ..
- Do you have any criminal records? If yes, please clarify ..
Written answers (4)
- Can you share an example of a Search, Product Page, or Reviews feature you owned in a live product? What metric did you improve, what were the results before and after, and how did you measure the impact of your changes?
- Share one decision you made differently, or one thing you shipped faster, because of AI. What did the AI do, and what did you do?
- Describe one decision you made with a data science or machine learning team on search, ranking, or recommendations. Which part was your call, and which was theirs?
- Please provide us with the names of two references in your previous or current work ...