Top Remote Jobs in Warsaw

Design, build, and optimise Java applications; support component design and deployments; implement CI/CD and testing at all levels; collaborate with client teams and technical leaders to deliver scalable, production-quality solutions.

Manage end-to-end recruitment for blue- and white-collar roles across Eastern Europe: take briefs, post adverts, source and interview candidates, manage offers and handover to HR. Support multiple countries (Hungary, Czechia, Poland, Slovakia), run TA projects, and liaise with stakeholders across divisions. Hybrid role requiring regular on-site work and occasional travel.

Design, implement, and productionize Databricks and ADF data pipelines; develop and version data models; manage Azure cloud data infrastructure; execute schema and data migrations; optimize ETL performance and complex data flows; support DevOps practices and collaborate on testing and deployment. Power BI experience is a plus.

Lead a remote backend team of 4–5 engineers owning a high‑traffic Ruby on Rails backend for mobile-first consumer apps. Translate product goals into technical roadmaps, improve scalability, performance, caching and real‑time features on AWS, oversee deployments/CI, mentor engineers, and handle incident debugging and documentation.

Lead and develop a high-performing team focused on AI enablement capabilities, enhancing internal engineering processes, and aligning product development with organizational goals.

Lead development of internal platforms and tools (back-office, acquisition, monetization), shape AI-driven acquisition systems, collaborate with engineering, data, monetization and operations, ensure reliability, scalability, and measurable business impact, and own features end-to-end.

Hands-on platform engineering role building and operating an internal Agentic AI platform: implement infrastructure-as-code, security and secrets management, GitOps delivery, observability, autoscaling, API/AI gateway routing, and run day-to-day operations including incident response, backups, and runbooks.

Lead and grow an MLOps team, define the ML infrastructure roadmap, and architect scalable automated pipelines, low-latency model serving, feature stores, monitoring, and CI/CD to move research into production.

Manage fund-related projects end-to-end: prepare conferences, build investor and partner databases, update presentations and trackers, support financial models and fund analytics, research counterparties, maintain deal pipeline, and coordinate deal scoring and internal reporting.

As an AI Engineer, you will build LLM systems, maintain AI solutions, collaborate across teams, and refine infrastructure integration while ensuring system uptime and accuracy.