Remote Cloud Native Engineer

Description:

• Kiratech offers its expertise to businesses looking to improve their quality and competitiveness by adopting a PlatformOps approach.
• The company assists clients in their journey of infrastructure and application modernization through its services and by selecting the best technologies in Platform AI, Platform Engineering, and Platform Security.
• Kiratech is seeking a Cloud Native Engineer specialized in AI for its Engineering Team.
• The role involves actively contributing as part of a team on projects at Kiratech's clients, focusing on the adoption of data science and machine learning engineering technologies and practices in a Platform and Cloud Native environment.
• The ideal candidate has solid experience in defining and implementing cloud solutions for ML and AI, a strong background in Cloud Native architectures, and leadership skills to coordinate multidisciplinary teams and interface with technical and business stakeholders.
• This position requires an individual capable of driving innovation with a practical approach to Cloud & AI technologies, a mindset oriented towards scalability and automation, and a strong ability to adapt to rapidly evolving technological scenarios.

Requirements:

• The candidate must have experience in managing the lifecycle of ML models, including Model Engineering, Deployment, and Monitoring.
• Knowledge of MLOps tools such as MLFlow, Kubeflow, TensorFlow, MetaFlow, Vertex AI, SageMaker, and Azure ML is required.
• Integration of AI with DevSecOps practices using tools like SonarQube, Snyk, Trivy, and other security and compliance tools is necessary.
• Competence in Data Analytics and AI-driven monitoring tools such as Prometheus, Loki, Elastic Stack, and Grafana is essential.
• Familiarity with modern data architectures to support training and inference of AI models and LLMs is required.
• Experience in managing or integrating tools for Data Lake, Data Mesh, and ETL is desired.
• The ability to design efficient and optimized pipelines for processing structured and unstructured data, focusing on quality, deduplication, and enrichment for AI models is preferred.
• Proficiency in Python for creating ML/AI libraries and SDKs, and Go for the Platform component is necessary.
• Knowledge of Apache Spark, Kafka, Flink, Neo4j, and OpenAI API for AI and Big Data is required.
• Experience with CI/CD pipelines for ML using GitHub Actions, GitLab CI, Jenkins, Keptn, and ArgoSuite is essential.
• Experience with Cloud Native architectures (AWS, Azure, Google Cloud) and managing scalable infrastructures for AI/ML is required.
• Mastery of Infrastructure-as-Code tools such as Terraform and Ansible, and GitOps methodologies like Flux and ArgoCD is necessary.
• Advanced administration of Kubernetes and container orchestration (CKA required) is essential.
• Knowledge of Red Hat OpenShift AI and containerized environments for AI workloads is preferred.
• Experience as a technical manager in consulting, R&D, or enterprise AI/ML contexts is required.
• Familiarity with Service Management and Project Management methodologies (ITIL, PRINCE2, AgilePM) is necessary.
• Leadership skills in managing cross-functional teams and coordinating complex projects are essential.
• A good command of the English language from a professional standpoint is required.
• Certifications or demonstrable experience in AI tools for software engineering practices and integration of AI in software is a plus.

Benefits:

• Continuous training is provided, with one day per month dedicated to learning through dedicated platforms.
• Employees can work from anywhere for one month each year or four weeks.
• A "Recharging Friday" is offered, which is a paid Friday off each quarter.
• Employees benefit from a supportive work environment.
• Electronic meal vouchers are provided.
• Corporate welfare programs are available.
• The position offers the opportunity to work in a young, dynamic, and technologically innovative company environment.