Your opportunity

This role sits within a climate technology company operating at the intersection of atmospheric science, machine learning, and large-scale cloud systems. The organization develops cloud-native data platforms and production machine learning systems designed to analyze environmental and sensor-driven data to reduce real-world wildfire risk.

You will design, build, and operate the cloud infrastructure that powers mission-critical environmental risk modelling and data processing. The platform supports structured and unstructured data storage, containerized compute, backend APIs, and map-based visualization used by internal teams and external stakeholders.

As the company expands its data sources, geographic coverage, and product capabilities, you will ensure the architecture remains modular, scalable, secure, and cost-efficient. Success in this role means enabling standardized patterns for new pipelines and services, fully automated deployments, strong observability, and predictable scaling as workloads and data volumes grow.

Key responsibilities 

• Architecture Ownership: Design and evolve a modular, layered cloud architecture with clear abstraction boundaries across storage, compute, services, and interfaces

• Platform Operations: Build, deploy, and operate containerized workloads and orchestrated workflows supporting data processing and backend services

• Scalability & Reliability: Own system scalability, availability, disaster recovery planning, and performance optimization across production environments

• Infrastructure Automation: Implement and maintain Infrastructure as Code, CI/CD pipelines, and automated deployment workflows to enable repeatable, low-risk releases

• Observability & Incident Response: Establish monitoring, logging, alerting, and incident management processes to ensure operational transparency and resilience

• Security & Compliance: Design and enforce secure-by-design infrastructure including IAM, networking, secrets management, and auditability controls

• Cloud Cost Management: Monitor and optimize cloud resource usage with clear visibility into cost drivers and efficiency opportunities

• Cross-Functional Platform Delivery: Partner with data, backend, and frontend teams to deliver scalable, production-ready platform capabilities

Tech Stack

• Backend: Python (Flask, Django, FastAPI)

• Containers: Docker

• Orchestration: Kubernetes

• Cloud Platforms: AWS, Google Cloud, Microsoft Azure

Your know-how

• Strong experience designing, building, and operating cloud architectures in production environments

• Advanced Python backend development experience

• Hands-on experience with Docker and container orchestration systems such as Kubernetes

• Experience implementing Infrastructure as Code and CI/CD systems

• Solid understanding of databases, object storage, APIs, and distributed data processing patterns

• Experience with monitoring, observability tooling, and incident management in live systems

• Knowledge of cloud security best practices and high-availability system design

It’s a bonus if

• You have experience working with geospatial or environmental data systems

• You have worked in platform engineering or multi-cloud environments

• You have optimized cloud costs in high data volume production systems

Interested in learning more?

Please send your resume or LinkedIn profile URL to talent@lutrapartners.com with “Cloud Architect – Data & ML Infrastructure” as the subject line. One of our talent partners will be in contact shortly.