Hiver
Hiver
51 – 200 Darbuotojai
B2BDirbtinis intelektasSaaS
Hiver yra dirbtiniu intelektu grindžiama SaaS įmonė, kurianti įvairiakrypčio klientų aptarnavimo programinę įrangą verslui. Jos platforma pradėjo veikti kaip su „Gmail“ integruota pagalbos tarnyba ir išsiplėtė į „Hiver Omni“ – vieningą darbo erdvę el. paštui, pokalbiams, „Slack“, balso skambučiams, „WhatsApp“ ir savitarnos portalams valdyti. Hiver dirbtinio intelekto funkcijos apima „AI Agents“, „AI Copilot“, „AI Help Center“, „AI Insights“ ir „AI QA“. Jos padeda rūšiuoti užklausas, rengti atsakymų juodraščius, atlikti kelių etapų veiksmus prijungtose verslo sistemose ir prižiūrėti žinių bazę. Produkte derinamos bendros pašto dėžutės, vidinis bendradarbiavimas ir integracijos su tokiais įrankiais kaip „Salesforce“, „Shopify“ ir „NetSuite“. Hiver aptarnauja klientų aptarnavimo, finansų, IT paslaugų valdymo ir žmogiškųjų išteklių komandas, o įmonė teigia, kad jos platformą naudoja daugiau nei 10 000 komandų. Auganti komanda kuria dirbtinio intelekto, klientų patirties, SaaS infrastruktūros ir įmonių programinės įrangos sprendimus sudėtingoms pagalbos operacijoms.

Senior Backend Software Engineer III

Senior backend engineer role focused on scaling distributed systems and AI capabilities at Hiver’s customer service platform. Build reliable APIs, model-serving pipelines, and collaborative support features.

Aprašymas

  • Scale backend platforms for rapidly increasing traffic and AI workloads
  • Develop low-latency inference and retrieval APIs, caching systems, and model-serving pipelines
  • Strengthen reliability, resilience, and performance across monolithic and microservices architectures
  • Use Kafka and RabbitMQ to create high-throughput, event-driven data pipelines
  • Work with ML and AI teams to deploy embeddings, rerankers, RAG solutions, and evaluation processes
  • Deliver features across backend APIs, domain models, and data pipelines from design through release
  • Embed AI recommendations, copilots, and retrieval-based workflows into the product
  • Partner with product and design teams to create consumer-grade user experiences
  • Build secure, compliant workflows for structured and unstructured customer data
  • Own observability through tracing, metrics, dashboards, feature flags, and SLOs
  • Lead investigation of complex problems spanning frontend, backend, infrastructure, and model pipelines
  • Run postmortems, identify root causes, and implement improvements to engineering processes

Reikalavimai

  • At least five years of experience building and scaling production systems end to end
  • Strong backend development experience with Go, Java, Python, or Ruby on Rails
  • Thorough knowledge of distributed systems, concurrency, performance optimization, and resilience
  • Experience with SQL and familiarity with NoSQL databases and caching systems
  • Exposure to production model serving, including embeddings and inference APIs
  • Strong cloud infrastructure fundamentals, preferably with AWS
  • Experience working with containers and CI/CD pipelines
  • Experience delivering AI systems or features to production is an advantage

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