Top Tech Jobs & Startup Jobs in Hungary

Provides technical leadership for Python-based AI backend platforms supporting LLM integrations, generative AI pipelines, and agent orchestration. Architects scalable AWS systems using FastAPI, Lambda, and EKS; establishes observability and engineering standards; drives performance, security, and reliability improvements; mentors engineers; and influences organization-wide technical strategy, platform capabilities, and best practices.

Engage eligible merchants about financing options, assess their needs and eligibility, collect documentation, qualify and hand over leads, and guide customers through risk and approval processes. The role also handles financing inquiries, maintains accurate records, coordinates with internal teams and partners, and supports process improvements and financing campaigns.

Provides advanced administrative support, including calendar and meeting management, scheduling, expense reporting, travel arrangements, presentations, records maintenance, budget assistance, visitor coordination, and employee onboarding. Coordinates administrative activities across departments and supports multiple employees. Works independently on complex assignments, resolves administrative issues, and may guide other administrative staff.

Develop and maintain Linux-based build environments, GitLab CI machinery, Jenkins workflows, automated test execution, and software packaging. Investigate build, test, and pipeline failures; provide technical support to product developers; improve CI reliability, usability, and performance; and document solutions and working practices. The role requires Python, Linux, Bash, SQL, Git, GitLab, and Jenkins experience, with CMake and Podman as advantages.

Develop and maintain production web scrapers in Python for SEON’s real-time data enrichment platform. Investigate cross-component issues, work with proxy infrastructure, write comprehensive tests, participate in incident response, and apply reliability, observability, and SRE practices. The role includes code reviews, deployment pipeline work, AI-assisted development, and collaboration with backend, infrastructure, and product teams. Candidates should have 1–2 years of software engineering experience or equivalent project experience, web scraping exposure, and foundational networking knowledge.

Provide frontline technical support to customers, educate users on product features, troubleshoot and resolve software and hardware issues, manage support cases, collaborate with engineering and customer-facing teams, improve support processes and documentation, and participate in an occasional off-hours on-call rotation.

Manage Wise’s Bank Account & Access Management controls across bank accounts, authorized signatories, user access, and payment activities. Responsibilities include onboarding and offboarding accounts, maintaining accurate records, reviewing requests, preparing operational and control-effectiveness reporting, updating documentation, supporting process improvements, and addressing internal and external audit requests. The role collaborates with Treasury, Banking, Operations, Risk, Controls, Product, Engineering, and audit stakeholders in a SOX control environment.

Conduct outbound phone and email engagement with German-speaking financial advisers, identify their needs and qualify commercial opportunities for senior sales colleagues. Build initial client relationships, maintain CRM records, and collaborate on opportunity handoffs. The role includes structured training in financial markets, investment solutions, portfolio analytics, and sales techniques, with a focus on technology-enabled business development in the German advisory market.

Own technical support for OEM and publisher partners, investigating revenue, inventory, ad-serving, tracking, feed-ingestion, and content-categorization issues. Use SQL, Kusto, BigQuery, monitoring tools, and AI tooling to diagnose production problems, build alerts and internal automation, support on-call incident response, and collaborate with R&D and Product on root-cause resolution.

Build and maintain internal machine learning platforms, distributed data processing solutions, reusable tooling, and large-scale data pipelines. Improve system reliability, performance, automation, and maintainability while collaborating with data scientists and engineers to productionize machine learning solutions. Contribute to architecture and engineering practices, and mentor teammates.