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 a person 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:

• Strong knowledge and skills in Machine Learning & MLOps, including experience in managing the ML model lifecycle (Model Engineering, Deployment, Monitoring).
• Familiarity with MLOps tools such as MLFlow, Kubeflow, TensorFlow, MetaFlow, Vertex AI, SageMaker, and Azure ML.
• Integration of AI with DevSecOps practices using tools like SonarQube, Snyk, Trivy, and other security and compliance tools.
• Competence in Data Analytics and AI-driven monitoring tools such as Prometheus, Loki, Elastic Stack, and Grafana.
• Knowledge of modern data architectures to support training and inference of AI models and LLMs (RAG, Vector DB, Feature Store).
• Experience in managing, implementing, or integrating tools for Data Lake, Data Mesh, and ETL is preferred.
• 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.
• Knowledge of Apache Spark, Kafka & Flink, Neo4j, and OpenAI API for AI and Big Data.
• Experience with CI/CD pipelines for ML using GitHub Actions, GitLab CI, Jenkins, Keptn, and ArgoSuite.
• Optimization and utilization of AI-driven software engineering practices.
• Experience with Cloud Native architectures (AWS, Azure, Google Cloud) and managing scalable infrastructures for AI/ML.
• Mastery of Infrastructure-as-Code tools (Terraform, Ansible) and GitOps methodologies (Flux, ArgoCD).
• Advanced administration of Kubernetes and container orchestration (CKA required).
• 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.
• Familiarity with Service Management and Project Management methodologies (ITIL, PRINCE2, AgilePM).
• Leadership in managing cross-functional teams and coordinating complex projects.
• Good professional knowledge of the English language.
• Preferred qualifications include certification or demonstrable experience in AI tools for software engineering practices and integration, Red Hat OpenShift AI, and various AI and Big Data tools.

Benefits:

• Continuous training: One day per month dedicated to training using dedicated platforms.
• Working from anywhere: One month per year or four weeks.
• Recharging Friday: One paid Friday per quarter.
• Friendly work environment.
• Electronic meal vouchers.
• Corporate welfare.
• Work in a young, dynamic, and technologically innovative company environment.