Python programmer állások, munkák Budapesten

• Üzleti igények összegyűjtése és elemzése
• IT rendszerek és szoftverek elemzése
• Fejlesztési igények meghatározása
• Funkcionális és technikai specifikációk készítése
• Üzleti célok és IT megoldások közötti összhang biztosítása
• Szoftverfejlesztési életciklusban való aktív részvétel

• Leading and developing the three-person QC function including workload planning, prioritization and performance management
• Defining daily and weekly QC priorities based on project deadlines, production capacity and quality risk

• Configuration of the P&P platform end to end across frontend and backend
• Tuning and optimization of forecast and attribution models to match client data and business logic
• Writing custom business logic in SQL, Python, or Go for non-standard configurations

• Contribution to successful delivery of client engagements focused on banking strategy and innovation
• Crafting long-term strategies
• Identification of new growth opportunities within and beyond clients' core businesses
• Building digital enterprises

Szakmailag irányítod és összefogod az analitikus CRM és lakossági adatmenedzsment terület munkáját, biztosítva az analitikus szakértők szakmai támogatását, fejlesztését és feladataik összehangolását....

• Design and build agentic systems that plan, call tools and automate real business workflows
• Develop LLM-powered applications including RAG pipelines: chunking, embedding, retrieval strategies, evaluation and iteration

• 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

• CI/CD-folyamatok tervezése, felépítése és üzemeltetése (Azure DevOps, GitLab CI, GitHub Actions vagy Jenkins)
• Infrastruktúra kezelése kód formájában (Terraform, Bicep/ARM, Ansible)
• Konténeres környezetek felépítése és üzemeltetése (Docker, Kubernetes / AKS)

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Development of highly scalable services realizing AI/ML functionalities

• Implementation and maintenance of large-scale data pipelines and the Azure/Databricks data platform
• Building robust, scalable pipelines using Azure Databricks (PySpark / SQL)
• Design and enforcement of data architecture standards including Delta Lake / Lakehouse architecture and data modeling

• Embedding in the daily life of up to three engineering teams: Customer Platform and Scoring
• Ensuring technical design alignment with SEON's architectural best-practices
• Ensuring security, scalability, and compliance in technical designs

• Building and maintaining the GRC Brain (AI reasoning layer) and Agentic Cortex (agent orchestration framework)
• Designing and implementing a 7-agent architecture including OnboardingAgent, ScopeAgent, StandardsMapper, RiskQuantifier, PolicyAnalyzer, InfrastructureAuditor, and ComplianceMonitor

• Creation of 3D rigs for different types of objects, animals and characters
• Collaboration with the visual effects supervisor and Lead CG to determine the best possible technical and creative approaches
• Delivery of work within established project targets and high quality standards

• Use formal verification algorithms to formally prove the correctness of complicated logic problems
• Identify key behaviors for verification to write clear testplans for complex designs
• Implement testplans using innovative formal techniques
• Drive tools to realize their best performance

• Ownership of data engineering features, architecture, and code quality
• Design, implementation, and maintenance of Databricks-based data pipelines and workflows
• Building and optimization of ETL/ELT processes using Apache Spark on Databricks

• Partnering with engineering teams to automate and optimize service availability, scalability, performance, monitoring, and alerting
• Developing software to automate the toil required to keep SaaS offerings highly available, scalable, and resilient

• Architect and lead the development of large-scale ML systems and model pipelines
• Introduction of new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
• Definition and driving of the ML technical roadmap in alignment with company objectives

• System IP microarchitecture specification and design
• SystemVerilog RTL verification and debug
• Formal bring-up of non-trivial IP blocks to achieve required quality levels

• Development, governance, deployment, and enhancement of liquidity analytics models and supporting infrastructure across asset classes
• Driving the analytics product lifecycle including prioritization, roadmap decisions, and deployment into production

• Implementation and improvement of business objects for mobile network infrastructure in backend systems up to the API layer
• Development and maintenance of business objects including data models, backend logic, and APIs