Data kft állások Budapesten (it programozás, fejlesztés)

• Partnership with Canvas Product and Engineering leaders to set overall strategy for platform experience for Admins and Educators
• Leveraging AI and emerging technologies to create innovative and intuitive product design experiences
• Overseeing a team of designers focusing on the Canvas product space

• Support the implementation of retail planning solutions for German-speaking clients
• Work with client teams to understand business requirements around planning, replenishment, and forecasting processes
• Translate business needs into system configuration and solution design

• 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

• Leading 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

• 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

• Design and propose changes to current data systems including migration paths and modernization strategies for legacy architectures
• Define and evolve the target architecture for data platforms covering ingestion, storage, processing, and consumption layers

• Delivery on complex data engineering projects across industries
• Leading small delivery teams
• Managing customer relationships alone or with a Project Manager
• Mentoring more junior engineers
• Evaluating the quality of junior engineers' work
• Contributing to hiring best-in-class data engineers

• Leading and growing multiple agile engineering teams
• Defining and owning the technical roadmap with stakeholders
• Championing responsible use of AI and automation
• Aligning technical strategy with business goals
• Mentoring and coaching engineers at all levels

• Chunking and ingestion architecture with deterministic, validation-gated pipelines handling diverse enterprise document types with indexing and contextual enrichment
• Retrieval pipeline with vector search, BM25 hybrid retrieval, RRF re-ranking, embedding model selection and optimisation

• Writing technical documentation for aiMotive's SW products and solutions in English
• Supporting SW development customer projects with user-centered content
• Preparing and editing internal process and developer documentation
• Close cooperation with Software Development teams and Product Management

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

• Design and implement core authentication and authorization including POST /auth/token endpoint, JWT validation middleware, and entitlement enforcement layer
• Build and maintain the entitlement decision cache with invalidation on entitlement changes

• Building and optimizing inference pipelines for large-scale model serving
• Working with frameworks like PyTorch, TensorRT, and vLLM to deploy models efficiently
• Implementing and optimizing ML models using techniques such as quantization, kernel fusion, and efficient batching

• Research, configure, and test AI tools including Claude, Gemini, Zapier, and n8n to improve the GTM stack
• Build proof-of-concepts for AI-driven lead research, automated email drafting, meeting summarization, and information hand-offs

• Design, implement, and optimize compiler passes and transformations using LLVM/Clang or GCC
• Build and maintain robust toolchains
• Support new and complex architectures in compiler backends
• Work on architecture-agnostic and IR-level optimizations
• Work on silicon specific optimizations

• 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

• Design and own end-to-end solution architecture across distributed systems and cloud environments
• Translate business requirements into scalable technical solutions with clear articulation of trade-offs

• Owning and continuously refining the product roadmap for a core part of Diligent’s governance, risk and compliance SaaS platform
• Owning end-to-end product strategy and roadmap for new Diligent business lines in AI, data analytics, and insights

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...

• Automation and database management including creation of technical specification documents and management of automations using Alteryx, Python, and SSIS
• Creation of reports and dashboards in Power BI
• Building data models and creating measures in DAX