Top Tech Jobs & Startup Jobs in Dublin

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.

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.

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.

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.