Responsibilities
- Design, implement, and operate cloud-native AI/ML services that are secure, reliable, and cost-efficient ensuring that they meet the business objectives and adhere to service level agreements (SLA).
- Deploy and maintainAI applications on cloud- architecture.
- Build retrieval-augmented generation (RAG) stacks: embeddings, vector stores, chunking, and evaluation.
- Create MLOps foundations: experiment tracking, model registry, CI/CD for data & models, and Infrastructure-as-Code.
- Investigate new techniques, tools, and methods that might increase efficiency among engineering & technology and cloud teams, as well as leading execution processes of topics evaluated & planned for roll-out.
- Collaborate with other technical leaders and business stakeholders to align all constraints and come up with solutions regarding project/product/initiative outputs.
- Be accountable for the reliability and security of cloud infrastructure and services.
- Provide visibility of performance, cost, and the security of cloud infrastructure and services.
- Drive continuous improvement, continuous delivery, and lean practices within the cloud team.
- Keep up to date on modern technologies and trends and advocate for their inclusion within products when it makes sense.
- Identify emerging technology solutions that reduce costs, increase efficiencies, enhance capabilities, reduce risk and improve security.
- Ensure that all cloud technology applications create a positive customer experience.
Requirements
- BS/MS degree in Computer Science, Engineering or a related subject.
- Proven hands-on software engineering experience.
- Strong experience in Java development.
- Strong experience with Spring Framework, preferably Spring Boot.
- Hands-on experience in designing and developing enterprise-grade backend applications.
- Solid understanding of microservice architecture and distributed systems.
- Experience with event-driven architecture and asynchronous integration patterns.
- Strong knowledge of scalable, resilient and high-availability system design.
- Solid understanding of object-oriented analysis and design using common design patterns.
- Experience with RESTful APIs and backend integration patterns.
- Experience leading highly skilled software engineers and supporting team growth.
- Ability to coordinate effectively across multiple teams and stakeholders.
Nice to Have
- Experience with containerized environments and CI/CD pipelines.
- Experience with monitoring, logging and observability tools in distributed systems.
- Familiarity with cloud-native architectures and modern backend infrastructure.
- Experience in performance optimization, system reliability and production support.
- Team Lead and Agile Scrum experience is a strong plus.
Work Arrangement
Hybrid
Additional Information
- Strong communication skills in English, both written and spoken.
