Phd hell ci javascript jquery állások IX. kerületben főiskolai végzettséggel

• Joining experienced engineering teams and contributing to existing projects while exploring and prototyping ideas for the future
• Gaining hands-on experience across the software development lifecycle with support from a mentor and the wider team

• Design, maintain, and evolve robust, scalable data architectures aligned with business and digital transformation objectives
• Build and optimize high‑performance data models for analytics
• Act as a strategic partner to business and engineering teams to shape data solutions end‑to‑end

• Definition of System Context
• Definition of external interfaces
• Align system requirements with stakeholders and create system architecture design based on them
• Support technical feasibility evaluation of system requirements
• Align and document architecture drivers and goals with stakeholders

• Designing and building artificial intelligence and machine learning solutions for enterprise clients
• Operationalizing artificial intelligence and machine learning solutions, combining custom models with cloud and third-party AI services to deliver production-ready outcomes

• Architecting complex AWS infrastructures and zero-day compliant landing zones
• Understanding customers’ business problems and providing technology consulting to identify the best-fit solution
• Owning the end-to-end solution as a key decision-maker and driving the delivery team

• Driving designing and building AWS infrastructure and landing zones
• Defining AWS infrastructure using Terraform or OpenTofu with Terragrunt, or AWS CloudFormation, and building CI/CD pipelines
• Leading migrations of customer workloads from on-premises (on-prem), GCP, Azure, or Heroku to AWS

• Conducting in-depth assessments with clients to understand their business and technical needs
• Analyzing client requirements and proposing feasible technical solutions based on them
• Identifying client challenges and goals, recommending effective solutions, and building client trust

• Technically managing a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Providing mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients

Manuális funkcionális, regressziós és exploratív teszteket hajtasz végre a heti szoftverbuild-eken a minőség és a kiadhatóság biztosítása érdekében....

• Analyzing business processes and collaborating with stakeholders to identify, assess, and prioritize automation opportunities
• Designing, developing, testing, and deploying scalable end-to-end automation solutions using UiPath, following industry best practices and enterprise standards

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)...

Building and maintaining production-grade AI infrastructure using Infrastructure as Code (Terraform/CDK), monitoring, logging, and deployment automation to enable fast and secure agent delivery...

Supporting the development and fielding of both patient preference and experience studies using relevant methodologies (qualitative and quantitative methods including but not limited to online surveys, DCE, BWS, thresholding etc.)...

• Taking part in the BAU development tasks
• Designing, implementing, and delivering high-quality software solutions that conform to architectural standards
• Optimizing and refactoring existing code for improved reliability and performance
• Understanding and reworking/improving the existing codebase

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...

Designing, optimizing, and extending transaction surveillance and data pipeline processes to enhance system efficiency, reliability, and scalability...

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

Providing scientific leadership within project teams independently and/or collaboratively with research scientists...

• 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)...