MARA is redefining the future of sovereign, energy-aware AI infrastructure. We’re building a modular platform that unifies IaaS, PaaS, and SaaS which will enable governments, enterprises, and AI innovators to deploy, scale, and govern workloads across data centers, edge environments, and sovereign clouds.
MARA is seeking a Principal IaaS Engineer to lead the architecture, standardization, and modernization of our global infrastructure-as-a-service platforms. This role blends hands-on technical leadership with strategic platform vision—defining the next generation of hybrid and cloud-native infrastructure across compute, storage, and networking domains. The Principal IaaS Engineer will partner closely with platform, data, and security teams to deliver high-availability, secure, and cost-optimized environments that power MARA’s mission-critical workloads.
The ideal candidate brings deep expertise in Infrastructure as Code (IaC), private and public cloud integration, and scalable datacenter operations. This individual will serve as a technical authority on multi-cloud architecture, automation frameworks, and high-performance storage and networking systems.
ESSENTIAL DUTIES AND RESPONSIBILITIES
- Design and evolve core compute, storage, and orchestration systems powering large-scale data and ML workloads.
- Drive implementation of secure, reliable, and scalable Kubernetes-based platforms, including Operators, CI/CD pipelines, and IAM systems.
- Collaborate with ML, product, and infrastructure teams to enable efficient data pipelines, feature stores, and training workflows across heterogeneous hardware.
- Own platform reliability through observability, automation, and proactive performance optimization.
- Define standards for deployment, validation, and operational readiness across environments.
- Lead vendor evaluation and integration for key technologies (Kafka, Snowflake, MLflow, Trino, etc.).
- Foster a culture of open-source contribution, innovation, and continuous learning.
QUALIFICATIONS
- 10+ years of software, systems, or data engineering experience; 3+ years in technical leadership or management.
- Proven expertise with distributed systems, data streaming (Kafka, Flink, Spark), and ML orchestration (Airflow, Kubeflow, MLflow).
- Strong proficiency in Go and Python with hands-on experience in Kubernetes, Docker, and Infrastructure-as-Code (Terraform, Ansible).
- Deep understanding of observability stacks (Prometheus, Grafana, ELK/FluentBit) and platform security.
- Experience delivering data migrations, hybrid cloud architectures, and large-scale CI/CD automation.
- Familiarity with modern data warehousing (Snowflake, Iceberg, Delta Lake) and vector databases (PgVector, Milvus, LanceDB).
- Track record of successful client delivery across multiple domains (cloud, media, industrial ML, or hardware integration).
- Excellent communication, cross-team collaboration, and mentoring skills.
PREFERRED EXPERIENCE
- Background in HPC, ML infrastructure, or sovereign/regulated environments.
- Familiarity with energy-aware computing, modular data centers, or ESG-driven infrastructure design.
- Experience collaborating with European and global engineering partners.
- Strong communicator who can bridge engineering, business, and vendor ecosystems seamlessly.
