Python állások VI. kerületben (ai és automatizáció)

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

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 agentic systems that do real work in production including tool-using workflows, RAG, structured outputs, guardrails, and measurable quality
• Working with Solution Architects and LLMOps focusing on building, making reliable, and continuously improving the system

Designing and implementing enterprise-scale data pipelines and advanced analytics dashboards, including solutions powered by artificial intelligence-enabled analytics tools such as Microsoft Copilot Agents and Claude...

• Improving operational efficiency through process optimization, automation, and the adoption of new technologies
• Understanding the company's data warehouse and helping align data flows with reporting requirements

• 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

Developing and implementing complex generative AI applications from discovery to deployment, realizing strategic, tactical, and operational impact...

• 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)

• 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

• Building and maintaining scalable cloud infrastructures using modern services and best practices
• Proactively detecting, analyzing, and fixing vulnerabilities and performance bottlenecks in cloud environments

Architecting and implementing scalable AI/ML solutions on Azure (preferred) or GCP, leveraging services such as Azure Databricks, Azure ML Studio, Data Lake Storage, Event Hubs and Functions (or GCP equivalents)...