Principal / Staff Software Engineer - Backend, MLOps and Cloud Infrastructure
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Nacre CapitalAgriTech
Portugal. Spain. Romania. Hungary. BulgariaFull-TimePrincipal
SalaryCompetitive salary and equity packages.
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Job Details
- Experience
- 9+ years of professional software engineering experience, with at least 3+ years spent operating at a Staff, Principal, or equivalent technical leadership capacity.
- Required Skills
- AWSDockerPythonKubernetesGrafanaPrometheusMicroservicesDatadogMLOps
Requirements
- Mastery of Python and deep experience building enterprise-grade backend systems and web applications.
- Proven track record in microservices architecture, API design, asynchronous event-driven patterns, and system scalability.
- Deep, hands-on expertise with AWS cloud infrastructure, networking configurations (VPCs, DNS, Ingress, Service Mesh), and infrastructure as code.
- Production-level mastery of Docker and Kubernetes for scaling and managing containerized workloads.
- Strong proficiency in database design, query optimization, and handling complex data lifecycles.
- Experience building or integrating machine learning infrastructure, model deployment pipelines, and ML feature stores.
- Expert knowledge in deploying logging, metrics, and tracing stacks including Datadog, Prometheus, Grafana, and ELK.
- 9+ years of professional software engineering experience, with at least 3+ years in a Staff, Principal, or equivalent technical leadership capacity.
- Demonstrated success in designing and operating large-scale distributed cloud systems from the ground up.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
Responsibilities
- Lead the architectural design, evolution, and scaling of distributed backend microservices and machine learning platforms.
- Establish, champion, and enforce engineering best practices across the organization, including rigorous code reviews, automated testing, design docs, and security protocols.
- Mentor and coach senior engineers, fostering a culture of technical curiosity, continuous learning, and high execution velocity.
- Design and implement high-performance, resilient, and secure cloud-native solutions using Python and modern web application frameworks.
- Drive the containerization and orchestration strategy using Docker and Kubernetes to ensure seamless deployments and efficient resource utilization.
- Build and maintain robust MLOps infrastructure to streamline the entire ML lifecycle.
- Own and secure AWS cloud infrastructure, optimizing networking setups including VPCs, DNS, ingress controllers, and service meshes.
- Architect end-to-end CI/CD pipelines and DevOps automation to facilitate reliable, friction-free daily deployments.
- Cultivate system visibility by implementing comprehensive observability stacks including Datadog, Prometheus, Grafana, and ELK.
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