Programozó állások XXI. kerületben (programozó, fejlesztő)

• Dotnet alkalmazások fejlesztése és karbantartása C# és .NET Core technológia használatával
• RESTful API-k és mikro-szolgáltatások fejlesztése
• Adatbázisok kezelése és optimalizálása
• Szoftverek teljesítményének javítása és hibák keresése
• Meglévő kódok refaktorálása

• Backend and frontend development with focus on high-performance and speed
• Cooperation with product team including UX, UI, and product management
• Building and coding backend in Node.JS and frontend in React in a complex web application
• Participation in and conducting code reviews

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

• Energiakereskedelmi folyamatokat támogató üzletkritikus alkalmazások, valamint szoftverkomponensek tervezése, fejlesztése és továbbfejlesztése
• Új funkciók implementálása, meglévő alkalmazások technológiai modernizációja
• API-k, User interfészek és rendszerintegrációk tervezése és fejlesztése

• Design and implement data fabric architecture across heterogeneous data sources and platforms
• Develop scalable ETL/ELT pipelines for batch and real-time data integration
• Integrate structured and unstructured data from databases, APIs, SaaS applications, data lakes, and enterprise systems

• Technológiai irányelvek és architekturális sztenderdek kialakítása és fenntartása;
• Rendszer- és alkalmazásarchitektúra tervezése a skálázhatóság, biztonság és teljesítmény figyelembevételével;
• Technológiai döntések támogatása és felülvizsgálata; új technológiák értékelése és bevezetése.

• Implementation of TypeScript features for AML services and customer facing Admin Panel
• Contribution to design discussions with informed questions and explanation of design decisions
• Independent scoping of work and early issue raising with requirements

• Design and build innovative AI solutions combining software development and data engineering
• Collaborate with global technologists, data scientists, and industry experts to transform businesses through analytics and AI
• Develop scalable data pipelines for machine learning and AI applications

• Writing production-quality, well-tested scraper code in Python
• Learning the architecture of the collection platform including scrapers, proxy layer, queues and enrichment API
• Debugging issues across multiple components using logging, monitoring and alerting tools

• Komplex LLM-, RAG- és agentikus AI-megoldások célarchitektúrájának megtervezése, szakmai irányítása és produkciós bevezetése.
• Coding agent skillek, MCP-szerverek, agent harness és runtime komponensek, routing-, memory-, tool- és evaluációs megoldások kialakítása.

• Design and build well-architected TypeScript features end to end for AML services and customer facing Admin Panel
• Lead team-level design reviews and write design docs or ADRs for significant changes
• Challenge requirements that don’t add up and raise delivery risks early with proposed mitigation

• Building and improving .NET applications
• Working closely with other devs, testers, and project managers
• Owning features end-to-end from concept to deployment
• Sharing knowledge and reviewing code
• Solving tricky problems

• Modeling and experimentation for fuzzy matching and AML screening quality
• Building evaluation datasets and metrics for match quality measurement
• Designing scoring and ML approaches for real-time decisioning

• Frontend development for a greenfield project with API integration
• Contribution to proof-of-concept tasks
• Collaboration with Senior Developers
• Test-driven development for code quality
• Close work with Product Design, Product Management, and Backend teams

• Development and support of backend applications
• Documentation and testing
• Connection and integration with external systems through APIs

• Development and improvement of computer vision algorithms for cricket tracking systems
• Building and enhancement of ball and player tracking solutions using multi-camera technology
• Contribution to multi-view geometry solutions to improve tracking accuracy

• Deployment and scaling of EcliptOS platform
• Ownership of EcliptOS platform delivery lifecycle
• Deployment and configuration of production-grade systems across cloud and hybrid infrastructures
• Validation of performance and stability of deployed systems
• Ensuring structured handovers for long-term success

Agentic AI development: Design and implement autonomous and semi-autonomous AI workflows, including planning, task execution, tool integration, context management, and fault recovery....

• Ownership of data models and storage architecture behind AI systems across relational, graph, and retrieval-oriented data
• Building and operating APIs, backend services, and pipelines to keep data current and accessible

• Client-facing communication
• Participation in pre-sales discussions
• Collaboration with sales and customer success teams
• Communication with clients' technical teams
• Design and configuration of data labeling and processing pipelines
• Combination of multiple data labeling components into automated workflows