Jobs at Constructor

Design the demo and onboarding experiences for Constructor's e-commerce product discovery platform. Own visual strategy, map interactions for AI/LLM features, produce high-fidelity mockups and assets, and ensure designs scale within the company design system to help customers go live faster.

Design, build, and maintain the foundational, high-scale search engine systems powering billions of daily requests. Work on backend infrastructure, deployment automation, capacity planning, observability, performance-critical code, and production operations while collaborating with a team to ensure reliability and scalability.

Own the end-to-end integration journey for developer customers and SIs, improving SDKs, tracking, validation tooling, and docs to reduce time-to-value, defects, and escalations while partnering cross-functionally and defining CDX+CDI KPIs.

Design, build, deploy, and maintain high-load, real-time ML-based ranking services and a Ranking Platform. Improve performance, feature delivery (feature store), CI/CD, and collaborate with DS, MLEs, and stakeholders.

Provide first-level technical support and onboarding for e-commerce customers integrating Constructor's platform. Guide API and library integration, troubleshoot issues, configure product index settings, communicate between customers and internal teams, and document processes to improve onboarding and integration resources.

Lead relevance evaluation and quality improvements by fine-tuning LLMs, building low-latency reranking and filtering systems, scaling LLM deployments, creating automated monitoring pipelines and agentic insights, and validating impact via A/B tests while collaborating with cross-functional teams.

Generate and qualify leads for the DACH region through personalized research and outreach, collaborate with Account Executives and Marketing, maintain Salesforce records, experiment with messaging and channels, and represent the company at events to build a strong enterprise pipeline.

Lead a cross-functional personalization team building production ML systems for search and browse. Own model design, user representations, embeddings, segmentation, offline evaluation, experimentation, and metrics-driven iteration. Hire, mentor, partner with product/engineering, and contribute technically to architecture and implementation to drive measurable retailer KPI improvements.

Own the product strategy and execution for demo and sandbox experiences that enable AEs/SEs to sell Constructor's AI-driven search. Build reliable, scalable demo flows, drive demo-readiness and reliability programs, prioritize demo requests, enable self-serve sandboxes, and incubate PLG opportunities to accelerate revenue.

Build and deploy production ML systems for large-scale ecommerce search and recommendations using text, image, and multimodal approaches. Tune and integrate LLMs and transformer models, develop end-to-end visual solutions, improve business KPIs through experimentation, and collaborate across teams to productize and scale ML capabilities.

Lead product strategy for pre-sales data solutions and data science integrations to accelerate proof-of-concept velocity. Own prospect data ingestion, automate collection and processing (including via LLMs/agents), enable model fine-tuning, build analytical tools and dashboards for AEs, and create internal self-service tooling while aligning cross-functional stakeholders to close enterprise e-commerce deals.

Generate and qualify leads for the Italian region, personalize outreach, start consultative conversations, maintain Salesforce records, collaborate with Enterprise AEs and Marketing, and attend occasional onsite events.

Lead and scale a Customer Success team across EMEA to drive customer adoption, retention, and expansion. Ensure successful go-lives, build executive relationships, implement scalable processes, act as escalation point for complex issues, partner with Product and Engineering to prioritise customer-impacting work, and continuously improve onboarding and optimisation to maximise customer value.

Analyze and instrument offsite discovery and SEO/GEO performance for ecommerce sites. Build integrations, ETL pipelines, and models to track organic and AI-driven traffic. Create tooling and frameworks for technical site audits, landing page modelling, SEO experiments, and enablement for product and customer teams.

Design, build, and optimize high-throughput, low-latency internal platform services (e.g., bot detection, rate limiting, traffic priority). Collaborate with product teams to deliver resilient, secure, code-driven solutions atop cloud infrastructure, using containers, CI/CD, and infrastructure-as-code.

Lead and scale the Offsite Discovery engineering team to build a high-performance, cost-efficient real-time personalization platform. Set engineering strategy, partner with product, hire and mentor engineers, define metrics and alerting, improve operational excellence, and collaborate across teams to drive measurable improvements in performance, cost, and product capabilities.

Design, deliver, and maintain high‑load real‑time recommendation web services. Implement IaC, CI/CD, observability, and stability testing. Collaborate with cross‑functional teams, integrate NoSQL/SQL and external services, and migrate features into distributed services.

Design, build, and maintain scalable backend services that deliver ML-enriched product attributes and badges. Develop high-throughput, low-latency APIs and manage a dedicated database, CI/CD pipelines, observability, and tests. Collaborate with ML engineers and cross-functional teams to ensure reliability, performance, and availability for downstream systems and customer dashboards.

Manage a mid-market sales territory and own the full sales cycle. Negotiate pricing, coordinate engineering/resources to close deals, perform deep discovery, use value-based selling to close six-figure deals, and provide product feedback to influence roadmap.

Lead the Recommendations engineering team to build scalable, reliable recommendation-as-a-service products. Own recommendation quality and business impact, set technical direction, translate product goals into engineering plans, ensure SLAs, hire and coach engineers, and drive system reliability and scalability.