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• Designing applications to meet business process and application requirements
• Building applications to meet business process and application requirements
• Configuring applications to meet business process and application requirements
• Collaborating and managing the team to perform effectively

• Shaping AWS-based cloud architectures and technical decisions for SaaS, PaaS, web application, and enterprise cloud environments
• Design and implementation of Infrastructure as Code solutions using Terraform, AWS CloudFormation, or Pulumi

• Delivery on complex projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• Design and develop distributed backend services using .NET and event-driven architecture
• Collaborate with product and commercial teams to turn engagement ideas into scalable, maintainable, and user-friendly solutions
• Optimize microservice ecosystem for performance, reliability, and observability

Development and enhancement of the MSCI Index Development Platform and the IndexMetrics Real-Time application using modern software engineering practices, Python, Azure, and AI-assisted development tools...

• Definition and development of system-level tests for high-end embedded computing systems
• Automation of test execution and evaluation through scripting in a CI environment
• Increase of test coverage by extending functional examples into comprehensive test suites

• Participation in design, POCs and development of complex tasks
• Ensuring high-quality delivery by developers
• Collaboration with architects to communicate, align and implement architecture direction
• Alignment with other tech leads to ensure technical consistency

• Design, development, and optimization of core ML models, especially in Computer Vision and Deep Learning
• Development of efficient, scalable training and inference pipelines
• Mentoring junior ML engineers, reviewing code and sharing best practices

• Technical consultation and client education
• Creation of feasible delivery plans for on-time, on-budget, and high-quality project implementations
• Design and implementation of high-performing, maintainable, and secure software aligned with industry best practices and company capabilities

• Fejlesztés, karbantartás és támogatás felhőalapú adatműveleti infrastruktúrában és termelési adatcsatornákban
• Tervezés, megvalósítás, működtetés és optimalizálás Azure-alapú adat-szolgáltatásokban és Databricks munkaterhelésekben

• Build-from-zero applications powered by the HawkAI Engine
• Bridge machine learning models and real-time data pipelines into APIs and user interfaces
• Integrate AI-assisted development tools into software architecture and data integrity workflows

• Lead frontend development of the application
• Deliver end-to-end features for web and mobile applications
• Occasional backend development
• Develop using frontend stack: React, React Native, Expo, Next.js, TypeScript, Supabase, React Query, Tailwind (NativeWind), React Native Reanimated, Skia

• Design of Azure cloud infrastructure to support Databricks and data platform workloads
• Implementation of Azure cloud infrastructure to support Databricks and data platform workloads
• Management of Azure cloud infrastructure to support Databricks and data platform workloads

• Technikai tanácsadás és támogatás
• Szakértői szintű iránymutatás nyújtása belső ügyfelek számára Azure-alapú megoldások tervezésében, megvalósításában és üzemeltetésében, a vállalati landing zone architektúrán belül

• Design and build scalable, reusable frameworks and services for data ingestion, transformation, and processing
• Develop and maintain the platform’s core capabilities such as orchestration, data quality validation, and schema management tools

• Design, build, review, test, and maintain Ruby on Rails features and services in line with Diligent’s agile engineering practices
• Own technical delivery for projects, epics, and major user stories, including solution design, implementation planning, and execution through to production

• Delivery of complex data engineering projects individually or by leading small delivery teams
• Management of customer relationships alone or in collaboration with a Project Manager
• Support of pre-sales process
• Mentoring of more junior engineers
• Contribution to hiring best-in-class data talent

• Design, develop, deploy, monitor, scale, and troubleshoot ML and LLM-based systems that power shared AI services across the platform
• Build secure, high performance microservices and platform components on AWS, owning services end-to-end from implementation through deployment and production monitoring

• Lead testing strategy and execution across complex microservices and frontend/backend architectures
• Design, develop, and maintain robust test automation frameworks integrating into CI/CD pipelines

• Owning the quality architecture for the Scoring engine
• Prioritizing test strategies based on real-world risk
• Standardizing reusable patterns for the repository
• Building reliable automated coverage across UI, API, and deep service layers