Senior DevOps – AI, Geospatial & HPC Infrastructure

Key Responsibilities

Infrastructure & Cloud

• Own and operate infrastructure across AWS and Azure

• Design, deploy, and maintain production-grade systems

• Manage Infrastructure as Code (Terraform)

• Ensure security, IAM, networking, and cost control

Backend & Platform Support

• Support production environments across Python, Node.js, and GraphQL services

• Ensure reliability of APIs and backend systems

• Handle asynchronous workloads and batch processing systems

Data & Geospatial Infrastructure

• Design and optimize data pipelines (EO, LiDAR, climate datasets)

• Maintain data lake architectures (S3, Parquet, GeoParquet)

• Optimize PostgreSQL / PostGIS performance

• Support geospatial and raster-heavy workflows (GeoTIFF, COG, MBTiles/PMTiles)

MLOps & Compute Systems

• Enable deployment and scaling of ML models (Python, PyTorch)

• Support training and inference pipelines

• Contribute to model lifecycle and monitoring

HPC & Distributed Workloads

• Operate and optimize HPC / distributed compute environments

• Handle job orchestration, scheduling, and parallel workloads

• Optimize performance, resource allocation, and compute efficiency

• Conduct benchmarking and scaling analysis

Observability & Reliability

• Implement monitoring, logging, and alerting (Prometheus, Grafana)

• Improve fault tolerance and incident response

• Ensure reliability of long-running data and compute jobs

Qualifications

• 5+ years in DevOps / Platform Engineering / Cloud Infrastructure

• Strong experience with:

  • AWS and/or Azure (compute, storage, networking)
  • Docker (required) and containerized environments
  • Terraform (or strong IaC experience)
  • CI/CD pipelines (GitLab CI preferred)
  • Linux systems and scripting

• Experience supporting data-intensive systems or pipelines

• Comfortable working with Python and Node.js environments

• Ability to work on or quickly adapt to HPC and distributed systems

• Strong ownership mindset and autonomy

Strong Pluses

• Experience with PostgreSQL / PostGIS

• Exposure to geospatial systems or EO data

• Experience with:

  • Airflow / workflow orchestration
  • Spark / PySpark
  • MLflow or model tracking systems
  • Ray or distributed compute frameworks

• Experience optimizing compute-heavy or batch workloads

• Familiarity with GeoParquet, COG, PMTiles, or large raster pipelines