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• In-depth assessments with clients to understand business and technical needs
• Analysis of client requirements and proposal of feasible technical solutions
• Identification of client challenges and goals with recommendation of effective solutions

• Technical management of a team of 2-3 AI and cloud engineers focused on fast prototyping of AI/ML solutions in AWS cloud
• Mentoring and technical support to junior and medium teammates
• Acting as a trusted advisor to clients
• Development of highly scalable services realizing AI/ML functionalities

• 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

• Embedding in the daily life of up to three engineering teams: Customer Platform and Scoring
• Ensuring technical design alignment with SEON's architectural best-practices
• Ensuring security, scalability, and compliance in technical designs

Shaping AWS architectures and technical decisions for web applications, SaaS platforms and enterprise environments...

• 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

• Partner with engineering teams to identify the highest-leverage AI opportunities in the developer workflow
• Own foundational architecture and standards for how agents model releases and internal tools are evaluated and deployed internally

• Implementation of complex ServiceNow solutions including system configuration and custom feature development
• Provision of advanced technical consulting and support quality assurance activities
• Ensuring adherence to implementation standards and technical best practices

• Partnering with engineering teams to automate and optimize service availability, scalability, performance, monitoring, and alerting
• Developing software to automate the toil required to keep SaaS offerings highly available, scalable, and resilient

• Building and maintaining simulation environments for mobile robotic perception and navigation
• Developing and integrating robotic behaviours and learning pipelines for reinforcement learning and motion planning in complex outdoor environments

• Aktív részvétel a tervezésben
• Specifikációk finomítása
• Fejlesztési feladatok megvalósítása
• Code review
• Automatikus tesztelés
• CI/CD folyamatok karbantartása (GitLab)
• Monitorozás és riasztások kezelése
• Alkalmazás karbantartása Kubernetes környezetben
• Junior fejlesztők mentorálása
• 1on1 meetingek tartása

• Design, develop, and deliver scalable, secure, and maintainable solutions on the ServiceNow platform
• Take end-to-end technical ownership of complex solutions from design and implementation to deployment and production support

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

• Vezetés a szoftverfejlesztés és tesztelés tervezésében, fejlesztésében, tesztelésében és telepítésében
• A teljes szoftverfejlesztési életciklus irányítása a követelménygyűjtéstől a terméktámogatásig

• Planning, implementation, development and testing of HW/SW components for the company backbone and data center networks
• Preparation of technical feasibility studies, design proposals and execution of POCs for the networks

• Adatfolyamok tervezése és fejlesztése robusztus, skálázható és biztonságos batch és real-time ETL/ELT folyamatok fejlesztésével
• Adatmodellezés telekommunikációs adatmodellek, adattárházak és adattavak logikai és fizikai tervezésével, struktúrájának kialakításával

• Development, testing, and continuous improvement of cloud-native CaaS and PaaS capabilities primarily using Go
• Contribution to Kubernetes operators and controllers that automate cluster and platform lifecycle processes

• Design, develop, test, and continuously improve cloud-native CaaS and PaaS capabilities primarily using Go
• Develop Kubernetes operators and controllers to automate cluster, platform, and application lifecycle processes

• Building and maintaining production-grade AI infrastructure using Infrastructure as Code, monitoring, logging, and deployment automation
• Optimising performance and cost efficiency of LLM workloads through autoscaling, caching, batching, and infrastructure right-sizing

• Design and implement cloud security controls across AWS, Azure, and/or GCP
• Deploy and tune Cloud Security Posture Management (CSPM) and Cloud-Native Application Protection Platform (CNAPP) tooling
• Build security into Infrastructure-as-Code and CI/CD pipelines