Software development engineer állások XIII. kerületben (it programozás, fejlesztés)

• Delivering independently Data Science projects with an end-to-end product-oriented mindset
• Engaging directly with clients to understand their business objectives and translate them into technical requirements

• Pentest folyamatok részleges automatizálása
• Sérülékenységvizsgálati eredmények AI-alapú feldolgozása
• Saját tudásbázis és RAG-rendszer kialakítása
• Pentest jelentések automatikus generálása
• Eredmények strukturálása, validálása és priorizálása
• On-premise LLM-alapú rendszer fejlesztése

• Designing, developing, and maintaining data ingestion and processing pipelines across different data platforms
• Developing and optimizing batch and streaming data pipelines using Python, SQL, and distributed processing technologies

• Leading a Core Modelling team building the foundational CAD engine that defines the Shapr3D user experience across all platforms
• Regularly reviewing and challenging engineering design documents, fostering an environment of collaborative problem-solving

• Providing troubleshooting, user support, and post-implementation assistance across supported HR applications
• Acting as a functional expert for SAP HCM and developing expertise across the broader HR application landscape

Working directly with clients, product owners, architects, and development teams to understand business and technical requirements and translate them into infrastructure and cloud architecture requirements...

• Leading a Snowflake migration project, supporting the migration of ETL pipelines between source systems and Snowflake
• Assigning tasks, tracking progress, and ensuring smooth day-to-day delivery

• Developing native Swift/iOS applications
• Designing user interfaces and functions as planned
• Taking part in requirements gathering, project and technical planning
• Writing Unit and UI tests, participating in developer testing
• Continuous learning

• Develop agentic AI applications from refined business and technical requirements.
• Implement agent workflows, prompts, model integrations, memory, RAG, tool calling, security controls, and human-in-the-loop steps.

• Designing agent roles, collaboration patterns, orchestration, models, memory, RAG, tool integration, identity, security, and human control
• Leading end-to-end delivery from discovery and proof of value through production rollout and scaling across business domains

• Developing native Android applications
• Designing user interfaces and functions as planned
• Participating in the definition of requirements and estimation of tasks
• Writing Unit and UI tests and participating in developer testing
• Staying up-to-date with current technology trends in Android development

Planning, implementation, development and testing of HW/ SW components for the company backbone and data center networks (Layer 2&3 networks interconnects company datacenters & cloud instances inside company as well as external partner/client networks)...

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management (CSPM) and Cloud-Native Application Protection Platform (CNAPP) tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines

Automatizálás és digitalizáció: a manuális hibakeresési, KPI-ellenőrzési és vizsgálati folyamatok kiváltása okos, automatizált megoldásokkal és scriptekkel...

Building agent workflows with LangGraph / LangChain / PydanticAI / CrewAI including routing, retries, fallbacks, timeouts, human-in-the-loop...

• Building scalable testing frameworks that enable the team to deploy confidently and maintain high system reliability
• Designing comprehensive test suites covering unit, integration, and acceptance testing that catch issues before they reach production

• Designing, developing, and implementing complex, scalable Lakehouse solutions on the Databricks platform across major cloud environments (Azure, AWS, or GCP)
• Designing, building, and optimizing modular data pipelines using Delta Lake to ensure data efficiency, reliability, and quality

Fejleszteni és megvalósítani összetett generatív AI alkalmazásokat a felfedezéstől a bevezetésig, stratégiai, taktikai és operatív hatás elérésével...

• Designing and implementing modern data architectures and lakehouse solutions (Databricks, Snowflake, Azure, AWS)
• Providing technical leadership throughout the project lifecycle and collaborating with business stakeholders

• Owning the architecture and delivery of production-grade LLM systems and classical ML solutions
• Designing, evaluating, and optimizing RAG pipelines (retrieval strategy, chunking, indexing, monitoring)