Geospatial Platform Engineer - AI focus

This role is responsible for developing and operating the underlying data, platform, and integration capabilities that support modern EO applications, including Retrieval-Augmented Generation (RAG) systems, agent-based workflows, geospatial data catalogs, and cloud-native data services.

You'll work closely with AI Engineers, Remote Sensing Scientists, Product Owners and external suppliers to transform prototypes into reliable, secure and scalable production services. You'll be based in Rome and report to the reference technical lead, who will mentor you as you progressively take ownership of platform design and architecture decisions.

This is an early-career position with a clear growth path toward technical ownership of our cloud-native geospatial and AI platform stack.

What you'll do

Introduce reusable AI capabilities across e-GEOS products and platforms, including SEonSE, AWARE, MapCy, AgriGeo, brAInt and other GeoInformation Centre services.

Transform existing prototypes and product-specific AI functions into secure, scalable and maintainable platform services and products.

Build shared data and knowledge pipelines combining EO data, metadata, documents and operational information.

Develop AI-assisted search, analysis, workflow automation, reporting and decision-support capabilities.

Build and integrate REST APIs, microservices and backend components that provide access to geospatial data, AI services, metadata catalogues and operational workflows.

Support deployment and operations of software and AI services on Kubernetes-based hybrid and cloud environments.

Contribute to platform capabilities enabling orchestration of AI agents, RAG, Vector Database, Large Language Models (LLMs), Geospatial Foundation Models (GFMs) and external services.

Develop CI/CD pipelines, automated testing frameworks and software delivery processes following DevOps and Platform Engineering principles.

Collaborate with AI Engineers to transition experimental prototypes into production-grade solutions with appropriate reliability, scalability and security controls.

Investigate and resolve performance bottlenecks, integration challenges and operational issues across platform components.

Draft and maintain technical documentation, architecture diagrams, operational procedures and integration specifications.

Contribute to evaluating emerging technologies in cloud-native geospatial computing, platform engineering, workflow orchestration and AI infrastructure.

Skills

Master’s degree in Software Engineering, Computer Science, Engineering, Mathematics, Physics, Geoinformatics or a related field, or equivalent experience.

Up to 5 years of professional experience in software engineering, cloud platforms, geospatial applications or platform engineering activities.

Solid software development skills, preferably using Python.

Understanding of modern web architectures, APIs, authentication mechanisms and service-oriented or microservice-based systems.

Familiarity with cloud platforms such as AWS or Azure.

Familiarity with containerization technologies and Kubernetes-based deployments.

Experience working with source control systems and collaborative development practices.

Understanding of CI/CD concepts and modern software delivery workflows.

Familiarity with DevOps and Platform Engineering principles.

Ability to analyse technical problems, investigate root causes and contribute to effective solutions.

Strong communication skills and ability to collaborate with engineers, scientists and external stakeholders.

A proactive attitude, willingness to learn and ability to progressively take ownership of technical deliverables.

Good Italian and English language skills.

Nice to have

Familiarity with Earth Observation, remote sensing or geospatial data management.

Experience working with STAC, OGC APIs, COG, Zarr, Rasterio, GDAL, Xarray or related geospatial technologies.

Familiarity with Retrieval-Augmented Generation (RAG) architectures and supporting platform components.

Experience integrating vector databases such as pgvector, Qdrant, Weaviate or Milvus.

Exposure to AI infrastructure, model serving platforms, inference APIs or LLM-enabled applications.

Experience with workflow orchestration platforms such as Airflow, Argo Workflows or Prefect.

Familiarity with GitLab, GitLab CI/CD and the Atlassian ecosystem.

Awareness of cybersecurity, secure software development and cloud security best practices.

Experience working with observability stacks such as Prometheus, Grafana, OpenTelemetry or similar technologies.

Contributions to open-source projects or participation in geospatial, cloud or AI communities.

What we offer

Our collective bargaining agreement is the CCNL "Industria Metalmeccanica Privata e della Installazione di Impianti"

Working mode: Hybrid

Contract category: Clerk

Thirteenth month;

Reward related to Business results;

Welfare vouchers;

Ticket of 8.50 euros

Opportunities for training and continuous updating of professional skills and soft skills;

Well-being: We put the economic, physical, social and psychological well-being of our people first, offering multiple solutions close to their needs.