Programozó állások XXI. kerületben (it programozás, fejlesztés)

• 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 own the Azure Native Data & AI Platform architecture
• Lead Azure Databricks platform implementation and evolution
• Define enterprise data, analytics, ML and AI platform standards and best practices
• Design Lakehouse and Medallion architectures

• 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.

• Részvétel nagyléptékű mérnöki és kivitelezési projektek digitálisan támogatott megvalósításában
• Támogatás projektjelentések és riportok készítésében és módosításában
• Előkészítés jelentések, dashboardok és projekt­dokumentációk belső és külső érintettek számára

• 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

• Leading data projects across the EMEA region including initiatives leveraging artificial intelligence and automation
• Leading and delivering innovation and transformation projects from scoping through to measurable business impact

• Integration of data from various sources into centralized data platforms
• Ensuring quality and availability of data across data pipelines and storage systems
• Support of implementation of data models and data warehouse solutions
• Monitoring data workflows and assisting in troubleshooting

• 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

• 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

• Design and build learner models including knowledge tracing and longitudinal approaches
• Shape the data foundation for learner modeling including defining relevant signals and building datasets
• Translate mastery and progression definitions into model targets and evaluation criteria

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

• Understanding business requirements
• Preparation and reconciliation of IT specifications including system design and logical design
• Cooperation with developer and testing team including participation in bug analysis, IT and business testing, and change management

• Operate, govern, secure, and continuously improve the Azure Databricks platform, ensuring reliability, scalability, security, and cost efficiency.
• Manage Databricks workspaces, environments, account-level settings, identities, and platform access controls.

• Assisting with latest projects
• Working with source code and applying development processes
• Attending online brainstorming sessions regularly
• Learning best practices and key technologies to quickly become productive

• Preparation of business concept and business strategy
• Review, analysis and evaluation of business systems, user requirements and processes
• Definition of business goals and KPIs
• Cooperation with developer and testing team
• Participation in User Acceptance Testing