Python programozó diákmunka állás, munka

• Defining and communicating architectural vision for the Cloud Management Portal aligned with product strategy and customer outcomes
• Making pragmatic architectural decisions balancing modern practices with delivery speed and customer value

• Magas szintű technikai és üzleti tanácsadás ügyfelek számára az Atlassian termékekkel és saját fejlesztésű megoldásokkal kapcsolatban
• Ügyfelek üzleti és IT folyamatainak felmérése
• Komplex megoldások tervezése, bevezetése és minőségbiztosítása

• Development and operation of Keycloak/RHSSO-based IAM capabilities on Kubernetes
• Standardization of deployment, configuration, and troubleshooting practices
• Continuous improvement of reliability, security, and automation around the IAM platform

• Active partnership with sales and project managers to estimate, design, develop and deliver solutions
• Continuous communication with domain experts and product owners to understand core business needs and goals to synthesize requirement and quality standards

• Experience in different data science topics
• Independent delivery of data science projects with product-oriented mindset
• Engagement with clients to understand business objectives and translate into technical requirements
• Leading pre-sales technical discussions

• Support the management of user permissions across multiple tools and systems including AWS IAM
• Help maintain and improve security tooling including endpoint protection solutions and infrastructure monitoring tools
• Assist with monitoring security alerts and investigating unusual events

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and curation of high-quality golden datasets
• Optimization of judge prompts for automated scoring
• Full-stack product development contribution
• Integration of automated evaluations into CI/CD pipelines

• Design of complex and scalable data solutions on the AWS cloud platform
• Development and implementation of complex and scalable data solutions on the AWS cloud platform
• Design and optimization of data pipelines
• Writing clean, efficient and maintainable SQL and Python code

• Architect scalable inference services, APIs, and backend components for model-driven and LLM-powered product features
• Productionize AI and ML workflows with strong MLOps practices
• Define and implement evaluation frameworks for model quality, system reliability, latency, and cost

• Design, build, and ship production retrieval systems
• Own vector store selection and operation including scalability, latency, reliability, cost, and multi-tenant design
• Build and operate indexing and refresh pipelines including chunking, embedding generation, backfills, deletes, and versioned indices

• Providing technical assistance and guidance to data engineering and machine learning community
• Taking ownership of difficult technical problems
• Participating in the vision for data engineering through documents and conversations
• Getting buy-in from stakeholders and leadership

Design and build knowledge tracing and longitudinal learner models that support mastery and progression features surfaced to customers...

• Build and operate multi-cluster containerized environments across cloud platforms
• Create end-to-end CI/CD pipelines for cloud-native applications and machine learning workloads
• Lead cost-optimization and FinOps initiatives for GPU, storage and data-egress spend

• Design and implement modern data architectures and lakehouse solutions
• Provide technical leadership throughout the project lifecycle
• Collaborate with business stakeholders
• Create effort estimations and provide technical expertise during the pre-sales phase
• Mentor 3-6 person project teams

• Lead the end-to-end implementation of data pipelines and GenAI applications on Databricks
• Design and maintain CI/CD, model serving, monitoring, and evaluation frameworks for AI production reliability
• Tune complex Spark jobs and LLM inference patterns for maximum efficiency and minimum latency

• Collaboration with cross-functional teams to create user-centered designs
• Design of intuitive and visually appealing interfaces for web and mobile applications
• Conducting user research, competitive analysis, and usability testing
• Creation of wireframes, prototypes, and high-fidelity mockups

• Leading complex penetration testing engagements
• Working with enterprise-scale cloud and Kubernetes environments
• Mentoring other security professionals
• Helping clients understand and reduce real-world cyber risks

• Monitoring configuration, maintenance and usage of environments with virtual machines and cloud based infrastructures (Kubernetes)
• Cooperation with platform engineers, software architects, delivery teams and operational units

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management and Cloud-Native Application Protection Platform tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines including IaC scanning and policy-as-code

• Line management, coaching, and career development for a team of Full-Stack Engineers
• Performance management and professional growth fostering
• Fostering a culture of technical excellence