Senior DevOps – AI, Geospatial

Role Overview

At Symbiose, we build the infrastructure layer to understand and value forests at scale using Earth Observation, AI, and High-Performance Computing (HPC). Our platform processes large-scale satellite (Sentinel, LiDAR), geospatial, and climate datasets to produce forest growth models, biomass estimations, and climate risk indicators. We are looking for a Senior DevOps / Platform Engineer to take ownership of the infrastructure powering these systems — across cloud, data pipelines, backend services, and HPC workloads. You will operate a data-intensive, geospatial, and compute-heavy platform in production. This is a unique opportunity to work with state-of-the-art stack.

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
• 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