Php hell ci javascript jquery állások IV. kerületben (ai és automatizáció)

Design of high quality Salesforce solutions leveraging the latest capabilities of the Einstein 1 Platform, Lightning Web Components, and modern Apex patterns...

• Design of evaluation framework for scalable LLM-as-a-judge pipelines
• Development of rubrics and datasets including comprehensive grading rubrics and high-quality golden datasets
• Optimization of judge prompts for automated scoring alignment

• Rendszerszervezői feladatok ellátása agilis csapatban
• Az IT folyamatok betartása és dokumentációk készítése és karbantartása
• Rendszeres kapcsolattartás az üzleti területekkel, együttműködés más IT Delivery Unit-okkal és a PMO-val

• Design and evolve robust cloud-native services and platforms with end-to-end ownership from ideation and prototyping to deployment, monitoring, and iteration
• Influence technical direction without direct authority by identifying architectural pain points and improving engineering standards

• AI-Native Infrastructure: Modern, GPU-intenzív AI/ML keretrendszerek szoftveres alapjainak megtervezése és kiépítése.
• Deep Containerization: Komplex Docker image-ek faragása, kifejezetten GPU-kompatibilis, AI workload-specifikus erőforráskezelésre (NVIDIA-docker, CUDA optimalizáció).

• 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

• Design and develop automation frameworks across frontend, backend, desktop, API, and data-driven systems
• Establish testing patterns and best practices for long-term maintainability
• Develop and maintain automated UI and end-to-end test suites using Playwright or Cypress

• Building and maintaining infrastructure for large-scale data and video streaming platforms
• Supporting development teams by making deployments easier, faster, and more reliable
• Improving security by helping to monitor and prevent potential risks

• 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

• Designing and developing new machine learning models with a focus on real-time performance
• Integrating cutting-edge ML features into the SkeleTRACK product
• Analysing model performance and identifying areas of improvement
• Mentoring junior engineers and driving technical discussions

• 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

• Setup and maintenance of IT cloud infrastructure for multiple products
• Setup and maintenance of the automated build/deployment jobs
• Maintenance of various support tools and utilities such as logs, monitoring, gathering user feedback
• Monitoring application performance and resource planning

• 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

• 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

• Real-time decision making with machine learning for risk assessments
• Ownership of risk infrastructure for Instant ACH in the US market
• Cross-functional collaboration with software engineers, data analysts, and data scientists

• 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

• Lead and cultivate engineering talent
• Provide hands-on technical leadership
• Own and drive the technical vision
• Master stakeholder relationships
• Champion Agile and technical excellence

• 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

• Scaling the platform that powers primary support channels including self-service, FAQs, and high-traffic chat interface
• Refining and scaling the support ecosystem leveraging Generative AI engine
• Engineering the logic and user experience connecting customers to AI capabilities

• Resource account igénylése és összekötése namespacekkel
• Resource accountba kerülő komponensek megvalósítása RDS, APIk, S3, MSK, cognito, SES, private link endpoint és endpoint service nonprod és prod környezeteken
• RICE API kapcsolatok kialakítása