Software development engineer állások X. kerületben (it programozás, fejlesztés)

Agentic AI development: Design and implement autonomous and semi-autonomous AI workflows, including planning, task execution, tool integration, context management, and fault recovery....

• Oracle adatbázisok telepítése, konfigurálása, üzemeltetése és monitorozása Linux alapú HA környezetben, RAC architektúrában.
• Adatbázisok teljesítményének mérése, hangolása és optimalizálása (SQL lekérdezések és adatbázis-műveletek optimalizálása, kapacitástervezés)

• Designing, developing, and deploying robust and scalable IAM services, including authentication, authorization, user provisioning, and directory services
• Leading technical discussions, conducting architectural reviews, and providing mentorship to junior and mid-level engineers on the team

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

• Leading end-to-end delivery of major enterprise platform and technology initiatives from inception through delivery
• Developing and owning detailed program and project plans, including timelines, milestones, dependencies, risks, and resource allocation across multiple concurrent workstreams

Lead identification of high-impact use cases for ML/AI/GenAI, prioritizing those that drive business performance, uncover optimization opportunities, and fuel revenue and margin growth....

• Investigate data quality issues, anomalies, reconciliation breaks, and inconsistencies across multiple systems.
• Perform structured root cause analysis (RCA) to identify underlying data and process issues.
• Trace data through different processing stages to understand where errors originate.

• Design, build and maintain enterprise Azure cloud infrastructure and platform services.
• Develop and maintain Infrastructure as Code solutions using Terraform.
• Design, implement and maintain Azure Landing Zones, governance policies and platform standards.

• Developing, customizing, and maintaining ServiceNow applications, modules, and integrations
• Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions

• Owning and evolving Tulip’s Cypress + TypeScript E2E automation framework, driving expanded coverage across critical product surfaces
• Integrating automated test suites into CI/CD pipelines to deliver fast, reliable feedback loops for engineering teams

• Writing and maintaining clean, high-quality, efficient and well tested code that aligns with project specifications
• Architecting and implementing key abstractions that bridge the gap between Software Engineering and DevOps

• Design and own the Azure Native Data & AI Platform architecture
• Lead Azure Databricks platform implementation and evolution
• Define enterprise data, analytics, ML and AI platform standards and best practices
• Design Lakehouse and Medallion architectures

Developing and executing a comprehensive vulnerability management program, encompassing regular scanning, penetration testing coordination, risk assessment, prioritization, and remediation tracking across all environments...

• Contributing to the test strategy and developing test plans for future Arm products
• Defining and improving the test architecture for automated testing and validation
• Developing test cases for embedded linux systems from first power on to end-to-end use cases

• Building tools and automation that help Wise's FinCrime teams develop and improve machine learning models
• Covering areas such as model experimentation, bias and fairness, automated training-set maintenance, and threshold analysis

• Contributing to both backend and frontend development, with a strong focus on performance, efficiency and speed to build something robust and stable
• Acting as a hands-on engineer, implementing backend solutions in Node.js and frontend features in React

• Act as the escalation point and lead investigator for high-impact data exceptions, breaks, and reconciliations.
• Systematically trace end-to-end data lineage across multi-hop data pipelines (ingestion, staging, transformation, reporting layers) to isolate defect origins.

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

• Meglévő rendszer továbbfejlesztése
• Új funkciók készítése
• Hibák javítása
• Régebbi részek refaktorálása szükség esetén
• Fejlesztési feladatok az adatbázistól a backend üzleti logikán keresztül a webes felületig

• Using formal verification algorithms to formally prove the correctness of complicated logic problems
• Identifying key behaviors for verification to write clear testplans for complex designs
• Implementing testplans using innovative formal techniques
• Driving tools to realize their best performance