Generix Group
SaaS, Collaborative Supply Chain solutions
SeniorDevOpsEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“Senior DevOps Engineer at Generix Group. Skills: DevOps, DataOps, MLOps, CI/CD, Azure, Docker, Kubernetes, Python, Bash, Terraform. designing, implementing, managing, and optimizing the infrastructure, automation pipelines, and workflows that support the entire lifecycle of software development, data processing, Analytics and machine learning model deployment. ensuring the reliability, scalability, efficiency, and speed of our development, data, analytics, and ML operations”
What You'll Achieve.
ensuring the reliability, scalability, efficiency, and speed of our development, data, analytics, and ML operations; make a meaningful impact on enterprise product quality
Industry & Context.
Troubleshoot and resolve complex infrastructure, pipeline, and deployment issues
What They're Looking For.
Must Have
Deep expertise in DevOps, DataOps, and MLOps principles, practices, and tooling, Mastery of CI/CD pipeline design and implementation for diverse artifacts (code, data, models), proficiency in cloud infrastructure management and automation (Azure), Expertise in containerization and orchestration (Docker, Kubernetes), scripting and automation skills (Python, Bash, etc. ), Experience with monitoring, logging, and observability tools (e. g. , Prometheus, Grafana, ELK Stack, Datadog), Understanding of data engineering concepts and data pipeline orchestration tools, Familiarity with ML model lifecycle management and associated tooling, 5+ years of experience in technical operations roles, with deep expertise in DevOps and demonstrable, hands-on experience implementing DataOps and MLOps practices, Proven experience with cloud platforms (mainly Azure, AWS is a plus), containerization (Docker, Kubernetes), CI/CD tools (e. g. , Jenkins, GitLab CI, ArgoCD), IaC tools (e. g. , Terraform), scripting (Python, Bash), data pipeline orchestration (e. g. , Airflow), and ML platforms (e. g. , MLflow, Kubeflow, SageMaker/Vertex AI), English or French Level: fluent
Nice to Have
AWS is a plus
What You'll Do.
and optimizing the infrastructure
and workflows that support the entire lifecycle of software development
Analytics and machine learning model deployment
ensuring the reliability
and speed of our development
and maintain robust CI/CD pipelines for software applications
data transformations (ETL/ELT)
and machine learning models (training
Implement and manage Infrastructure as Code (IaC) using tools like Terraform to ensure reproducible and scalable environments (cloud or on-premise)
Develop and automate data quality checks
data pipeline monitoring
and alerting systems within the DataOps framework
Establish and manage MLOps workflows including experiment tracking
automated model retraining
and performance monitoring (drift
Implement comprehensive monitoring
and alerting solutions across all systems and pipelines (applications
Champion and enforce best practices in security
and performance across all operational domains
Troubleshoot and resolve complex infrastructure
and deployment issues
Evaluate and recommend new tools and technologies to improve operational efficiency and capabilities
How You'll Work.
Team & Collaboration
fostering collaboration between teams; Collaborate closely with software developers, data engineers, data scientists, and analysts to understand their needs and provide operational support and tooling
Full Job Description
Generix is a leading SaaS vendor specializing in Collaborative Supply Chain solutions that enable the seamless exchange of goods and data across the globe between suppliers and customers, all while responsibly managing their flows. Its platform of innovative digital services optimizes the management of physical flows, by coordinating the entire supply process, from production to delivery, thanks to its WMS, TMS, RMS and VMI solutions; as well as logical and financial flows, by integrating the systems of all players in the chain, from order to payment, with its e-invoicing, e-reporting, EDI, P2P and O2C solutions. Generix creates a distinctive ecosystem designed to cater to its customers, ensuring top-notch performance and sustainability, connecting all global players in retail, industry and services, and fostering the transition toward greater digitalization and energy efficiency. With nearly 850 dedicated employees, Generix provides day-to-day support to over 4,500 companies across more than 60 countries, processes over 500 million invoices, handle more than 40 million order lines each month, and manage 8 million EDI messages daily. Our clientele includes Danone, FM Logistic, Fnac-Darty, Essilor, and Ferrero. This role is responsible for designing, implementing, managing, and optimizing the infrastructure, automation pipelines, and workflows that support the entire lifecycle of software development, data processing, Analytics and machine learning model deployment. This individual will be a key technical expert ensuring the reliability, scalability, efficiency, and speed of our development, data, analytics, and ML operations, fostering collaboration between teams and promoting best practices across DevOps, DataOps, and MLOps domains. Here's what you'll be doing: * Design, build, and maintain robust CI/CD pipelines for software applications, data transformations (ETL/ELT), and machine learning models (training, validation, deployment). * Implement and manage Infrastr
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