About the job
About Us:
At Quartermaster AI, we are committed to ensuring that the ocean is a secure and sustainably managed resource for all. Through innovative applications of AI, distributed sensing technologies, and robust data systems, we are pioneering capabilities that were previously unimaginable. Our open-ocean systems empower vessels and coastal infrastructures to sense, compute, and communicate, thereby enhancing maritime domain awareness for those who rely on it most.
Job Description:
We are in search of a highly skilled Senior Data Engineer with over 7 years of experience to architect, develop, and maintain secure, resilient, and scalable data systems that support mission-critical maritime and defense applications. The successful candidate will possess profound knowledge of AWS and Azure environments, distributed systems, and secure data architecture. Experience working with government contractors, military systems, or regulated environments is strongly preferred, along with a keen understanding of the operational demands associated with real-time, high-availability data platforms.
Proficiency in GIS, streaming architectures, SDR/radio systems, radar pipelines, maritime domain awareness systems, or military data management is highly advantageous.
Key Responsibilities:
- Design, develop, and maintain scalable batch and real-time machine learning, data science, and data export pipelines.
- Architect and oversee AWS and Azure cloud infrastructure.
- Administer and optimize databases including MongoDB and PostgreSQL within RDS and EC2-hosted environments.
- Implement replication strategies, failover systems, and resiliency management for high-availability operations.
- Design systems that distinctly separate public and private/classified data.
- Support high-throughput streaming ingestion and processing of sensor, radar, SDR, and maritime feeds.
- Develop infrastructure-as-code and automated deployment pipelines.
- Ensure secure-by-design architecture is aligned with compliance requirements.
- Provide guidance and architectural leadership for managing data at scale.
- Monitor performance, reliability, and cost optimization across environments.
- Collaborate with DevSecOps, AI/ML, and mission teams to deliver operational capabilities.

