Top Tech Jobs & Startup Jobs

Lead and grow an 8–10 senior-engineer team owning delivery, reliability, and architecture for a high-throughput web data collection product. Balance features, experiments, tech debt, and reliability; remove impediments; drive technical excellence, observability, and testing; report status to business and escalate strategic decisions.

Design, deliver, and maintain high-performance backend systems and web-scraping infrastructure at large scale. Mentor engineers, lead technical discussions and code reviews, own features from discovery to delivery in Agile workflows, troubleshoot complex issues, and contribute to product research and R&D.

Design, build, and maintain Python backend services for LLM-powered products. Implement RAG, semantic search, agent workflows, and API endpoints; integrate with vector/search/databases; optimize prompts, latency, cost, and reliability; collaborate cross-functionally and contribute to evaluation and testing of AI features.

Build and maintain high-scale backend services and product endpoints (Go-first), work across Node.js/TypeScript systems, design for distributed systems at massive scale, write tested documented code, collaborate on architecture and reviews, and apply AI coding tools in daily development.

Lead go-to-market, product positioning, and growth for a new product. Define growth strategies across acquisition, activation, retention and monetisation; run experiments (A/B tests, funnel optimisation); partner with Product, Engineering, Sales and Marketing; support enterprise client relationships and prioritise growth-impacting initiatives.

Own AI visibility strategy and execution across major LLMs and generative search engines. Drive citation growth, build measurement frameworks, optimize content and site structure for machine discoverability, and upskill internal teams. Collaborate with SEO, Content, Web, and Product to make AI-driven search a company-wide capability.

Lead the end-to-end roadmap for data products: design and ship multi-source datasets, productize ML/AI features, define customer-facing data quality SLAs, run discovery with customers, and coordinate cross-functional stakeholders while owning backlog and sprint planning.

Manage B2B customer relationships to ensure satisfaction and retention, identify upsell/cross-sell opportunities, coordinate internal teams to resolve issues, maintain CRM data, handle renewals and attrition risk, and advocate for the product while supporting revenue targets.