Jobs at GoodData

Lead customer-facing design and delivery of production-grade AI and agentic analytics on GoodData Cloud. Own discovery, prototyping, integration, and production handoff using semantic models, LLMs, embeddings, vector search, REST APIs, and local inference. Advise on architecture, governance, TCO, and multi-tenant secure designs while coordinating across product, consulting, sales, and support.

Design and implement backend microservices for an AI-native analytics platform, focusing on scalable distributed data processing, orchestration, and integration. Write high-quality, test-driven code in Python/Kotlin/Rust, deploy on Kubernetes, influence API design and best practices, and take end-to-end ownership while collaborating with product, architecture, and QA.

Design and implement BI and AI-powered analytics solutions on the GoodData platform. Lead solution architecture, data modeling, ETL design, dashboards, customer implementations, and coordination across consulting, product, sales, support, and training teams. Build trusted customer relationships, integrate LLMs and AI workflows, mentor colleagues, improve implementation methodologies, and support multiple engagements for US customers.

Drive full-cycle enterprise SaaS sales: source and close new business, run complex multi-stakeholder deals, own account growth (renewals, upsells, cross-sell), forecast accurately, and build regional presence via events and meetings.

Support integration, installation, and operation of a cloud-native platform on AWS/Azure and Kubernetes. Improve Helm charts, Terraform providers, GitOps, observability dashboards and docs. Collaborate on SaaS infrastructure, optimize Kubernetes operations using CNCF projects, Flux, and GitHub Actions, and leverage Grafana/Loki/Mimir/Tempo and AI tools to automate and troubleshoot deployments.

Design, build, and productionize multi-layered agentic AI systems (routers, tool-calling agents, RAG pipelines, evaluation, AI monitoring). Implement Python microservices on Kubernetes, optimize for scalability, performance, and security, and collaborate with cross-functional teams to transition AI solutions into production.