---
title: 'Senior Product Manager: Recall at Constructor'
canonical: 'https://feeny.ai/job/senior-product-manager-recall-constructor-emea-cxj8g6842m8j'
type: 'job'
last_seen: '2026-09-11'
---

# Senior Product Manager: Recall at Constructor

- **Company:** Constructor
- **Location:** EMEA
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-07-28
- **Last confirmed live:** 2026-09-11
- **Apply:** https://jobs.ashbyhq.com/constructor/7bc86d05-145d-4b7c-aa6e-b0b207d46117

## Job description

## About Us

Constructor powers product search and discovery for some of the largest retailers in the world. We serve billions of requests every week, and you’ve probably seen our results somewhere and used our product without knowing it. We differentiate ourselves by focusing on metrics over features, and reinventing search and discovery from the ground up as a machine learning challenge with the specific goal of improving metrics like revenue. We’re approximately doubling year over year despite the market slowing down and have customers in every eCommerce vertical. We’re a passionate team of technologists who love solving problems and want to make our customers’ and coworkers’ lives better. We value empathy, openness, curiosity, continuous improvement, and are excited by metrics that matter. We believe that empowering everyone in a company to do what they think is best can lead to great things.

Job Summary We’re looking for a highly technical, systems-minded Senior Product Manager to lead two critical search intelligence teams: Machine Learning & Recall and Query. Search at Constructor is fundamentally an ML challenge, and this role sits at the absolute entry point of our discovery pipeline, right where shopper intent meets candidate retrieval. In this role, you will bridge the Query team (understanding what a shopper means across intent, entities, and language) with the Machine Learning & Recall team (retrieving the exact right set of candidate products across massive catalogs). You will define strategy across both domains, balancing state-of-the-art techniques, such as vector search, semantic parsing, dense embeddings, and LLM-assisted query interpretation, with low-latency production execution. You won’t be measured on shipping features for the sake of it; you’ll be measured on candidate quality, query accuracy, and driving business outcomes like conversion rate, search-attributed revenue, and revenue per visit.

## What You’ll Do

- Set a unified roadmap: Define the multi-quarter vision and strategy across both the Machine Learning & Recall and Query teams, ensuring query understanding and candidate generation evolve hand-in-hand.
- Drive Query intelligence: Lead the Query team to push boundaries in tokenization, spell correction, entity extraction, intent classification, and LLM-assisted query parsing across multiple languages.
- Advance Recall systems: Lead the Machine Learning & Recall team in evolving candidate generation architecture, seamlessly combining traditional keyword search with modern dense embeddings, vector retrieval, and hybrid recall models.
- Move core business metrics: Own measurable lift in search-attributed conversion, revenue per visit, and GMV across all retail customer verticals.
- Turn research into production wins: Work shoulder-to-shoulder with ML researchers, data scientists, and software engineers to take SOTA models from research to low-latency, cost-effective production systems.
- Balance ML performance trade-offs: Make data-backed decisions balancing model complexity, accuracy, inference latency, compute costs, and real-time execution constraints.
- Build evaluation frameworks: Establish robust offline and online measurement systems to evaluate retrieval precision and query understanding accuracy against customer revenue outcomes.
- Orchestrate pipeline handoffs: Ensure candidate product sets and query context flow cleanly into downstream ranking and search quality models without signal loss.
- Solve systemic issues: Lead technical triage when query interpretation or retrieval anomalies occur, building durable, automated fixes rather than one-off patches.

What Success Looks Like Within your first year, you will have:

- Evolved our hybrid recall framework to measurably improve candidate generation precision for long-tail queries and complex catalog structures.
- Driven quantifiable lift in search-attributed conversion and revenue per visit across major customer verticals.
- Stood up an integrated evaluation framework connecting query parsing and candidate recall directly to business outcomes.
- Optimized inference latency and compute infrastructure to ensure high-capacity ML models run fast and cost-effectively in production.

## Benefits

- Unlimited vacation time - we strongly encourage all of our employees to take at least 3 weeks per year.
- A competitive compensation package including stock options.
- Company-sponsored US health coverage (100% paid for employee).
- Fully remote team - choose where you live.
- Work-from-home stipend! We want you to have the resources you need to set up your home office.
- Apple laptops provided for new employees.
- Training and development budget for every employee, refreshed each year.
- Parental leave for qualified employees.
- Work with smart people who will help you grow and make a meaningful impact.

This position is fully remote — [Constructor.io](http://Constructor.io) is a remote-first company.

Diversity, Equity, and Inclusion at Constructor At [Constructor.io](http://Constructor.io) we are committed to cultivating a work environment that is diverse, equitable, and inclusive. As an equal opportunity employer, we welcome individuals of all backgrounds and provide equal opportunities to all applicants regardless of their education, diversity of opinion, race, color, religion, gender, gender expression, sexual orientation, national origin, genetics, disability, age, veteran status or affiliation in any other protected group.

## About Constructor

## Core Business
- **Primary industry**: AI-powered ecommerce search and product discovery (SaaS)
- **Target customers**: B2B, enterprise ecommerce brands, retailers, distributors, and marketplaces
- **Mission/purpose**: To automate the rich complexity required for a modern search experience behind a simple, elegant SaaS solution, helping shoppers find what they want to buy using natural language and AI.

## Products & Services
- **AI Shopping Agent**: Natural language conversational agent that helps shoppers discover products and answer questions.
- **Search & Browse**: Personalized search and category browsing with reinforcement learning.
- **Recommendations**: Product recommendations for onsite, email, SMS, and mobile notifications.
- **Retail Media**: Sponsored products and ads that don’t sacrifice customer experience.
- **Merchandiser Controls**: Tools for merchants to manage rankings, promotions, and experiments.
- **Insights & Automations**: Dashboards, reports, and automated attribute enrichment using GenAI.
- **Answer Engine Assistants (Beta)**: Integration with ChatGPT and other answer engines for offsite discovery.
- **Merchant Intelligence Agent (Beta)**: Research and fix ranking issues.
- **Product Insights Agent**: Generate personalized product questions to help shoppers buy with confidence.
- **Collections**: Dynamic, curated product pages.
- **In-Store**: Extend online intelligence to physical stores.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private)
- **Key Metric**: $40.0M annual revenue (LinkedIn estimate); $86.1M total funding across 4 rounds
- **Notable Investors/Partners**: Not named in provided sources, but clients include Sephora, Under Armour, Petco, and many others.
- **Growth Signals**:
  - 336 employees (LinkedIn) / 375+ team members (company site), +48% YoY headcount growth
  - 400+ billion requests powered per year
  - 98.5% average client retention rate over the last three years
  - Named a Leader in Forrester Wave (Commerce Search & Product Discovery, Q3 2025), Gartner Magic Quadrant (Search & Product Discovery, 2025), and IDC MarketScape
  - Top rated on G2 Crowd and Gartner Peer Reviews (4.9 and 4.8 respectively)
  - 94% team member retention rate

## Competitive Advantages
- **AI-native from day one**: Built on clickstream data and advanced AI, not bolted onto legacy keyword search.
- **Reinforcement learning across touchpoints**: Every interaction (search, browse, agent) makes the system smarter.
- **API-first, headless, composable, platform-agnostic**: Easy integration with any tech stack.
- **Ecommerce-specific optimization**: Sole focus on commerce metrics (revenue, conversion, profit), consistently delivering $10M+ revenue lifts for customers.
- **Only vendor named a Leader by three independent analyst firms (Forrester, Gartner, IDC)**.

## Strategic Focus
- **AI agents and reasoning**: Expanding AI Shopping Agents, Answer Engine Assistants, and Merchant Intelligence Agents.
- **Offsite discovery**: Enabling discovery via email, SMS, and answer engines like ChatGPT.
- **In-store integration**: Extending online intelligence to physical retail.
- **Continued investment in personalization and automation** to reduce setup time (8 weeks or less).

## Why Work Here
- **Culture**: Remote-first, 100% remote – choose where you live. Collaborative, empathetic, and problem-solving environment. Rated top 5% on RepVue and a Will Reed Top 100 award recipient.
- **Benefits**:
  - Company pays 99% of medical, dental, and vision premiums for US team members.
  - Unlimited PTO and vacation time (minimum 3 mandatory weeks off per year).
  - Paid parental leave.
  - Yearly Remote Work Stipend + one-time $500 New Hire Setup Stipend.
  - Yearly Learning & Development $500 Stipend.
  - Stock options for every team member.
  - Company-issued Apple laptop.
- **Growth**: Fast-growing startup with opportunities to work on challenging AI/ML problems used by millions of shoppers. Mentorship, autonomy, and career development.
- **Diversity & Inclusion**: Committed to DEI with an internal ERG.
- **Team**: 94% retention rate; described as collaborative, brilliant people who enjoy solving hard problems.

## Sources
1. [Constructor Careers Page](https://constructor.com/about/careers)
2. [Constructor Main Website](https://constructor.com/)
3. [Constructor LinkedIn](https://www.linkedin.com/company/constructor-io)
4. [Constructor About Page](https://constructor.com/about)
5. [CB Insights Company Profile](https://www.cbinsights.com/company/constructorio) (used for funding and revenue data, though not directly cited in text – revenue from LinkedIn)

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