Job Description

About IRRI

The International Rice Research Institute (IRRI) is dedicated to reducing poverty and hunger through rice science; improving the health and welfare of rice farmers and consumers; and protecting the rice-growing environment for future generations. IRRI is an independent, nonprofit, research and educational institute, founded in 1960 by the Ford and Rockefeller foundations with support from the Philippine government. The institute, headquartered in Los Baños, Philippines, has offices in 17 rice-growing countries in Asia and Africa, and over 1,000 staff.

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Working with in-country partners, IRRI develops advanced rice varieties that yield more grain and better withstand pests and disease as well as flooding, drought, and other harmful effects of climate change.

Job Purpose

This position will develop a scalable cloud-based ORYZA computation system as the shared backbone for global simulation and MRV applications. It is capable of supporting global-scale (250 m–1 km resolution) continuous multi-season rice simulations. The consultant will also develop the AWS-based cloud architecture, containerize the ORYZA simulation engine, implement large-scale execution and orchestration frameworks, and build secure client-facing APIs for job submission, monitoring, and result retrieval with MRV. The ultimate goal is to enable global, high-resolution historical and seasonal (3–5 month) ORYZA simulations through an automated, cost-efficient, and robust cloud computation system.

Roles and Responsibilities

Design AWS cloud architecture for ORYZA large-scale simulations (e.g., AWS Batch, EC2, S3, IAM).
Define scalable compute and storage infrastructure for grid-based simulations.
Containerize ORYZA in a Linux-based Docker environment.
Develop a manifest-driven execution engine.
Implement per-grid-cell sequential simulation runner with state carry-over support.
Develop checkpointing and resume functionality.
Implement failure detection and recovery mechanisms.
Develop logging and monitoring framework.
Conduct system integration testing with model and data teams.
Develop secure client-facing APIs for:
- Data submission
- Job control and status monitoring
- Result retrieval
Implement authentication and access control mechanisms.
Develop automated job orchestration and scaling pipelines.
Optimize performance for large-scale parallel simulations.
Implement cost-efficiency strategies (e.g., spot instances, batching).
Harden security configurations (IAM, data encryption, logging, auditing).
Conduct regression testing and system validation.
Prepare full technical and operational documentation.
Support knowledge transfer to IRRI technical staff.
Develop an online dashboard as an MRV interface.
Develop full API integration with the ORYZA cloud system.
Implement scenario management workflows (water, fertilizer, cropping schedule).
Develop GHG quantification modules (CO2, CH4, N2O, GWP).
Design and implement spatial simulation workflows.
Develop reporting modules (inventory, summary, technical annex).
Implement data pipelines for climate, soil, and management datasets.
Support frontend-backend integration.

• Implement result visualization and export tools.

Qualifications

Bachelor’s or Master’s degree in Computer Engineering, Computer Science or a related technical field.
Minimum 7 years of professional software engineering experience within large-scale production environments.
Extensive background in designing and scaling distributed systems and data pipelines to support high-throughput applications.
Demonstrated experience in architecting and deploying cloud-native systems that handle complex data processing workflows.
Proven track record of building and managing end-to-end data systems, from ingestion and transformation to production deployment.

Skills Required

Mandatory

Strong expertise in AWS services (Batch, EC2, S3, IAM, CloudWatch) or equivalent cloud services (Google Cloud Functions, GCS).
Mastery of distributed compute frameworks and orchestration tools for batch and real-time processing.
Deep technical expertise in containerization and cloud orchestration to ensure reliability and scalability in production.
Strong proficiency in Python and other industry-standard backend languages such as Ruby on Rails, Java, or C++.
Proven ability to implement cost-efficiency strategies and performance tuning for massive data storage and compute clusters.
Practical knowledge of Infrastructure-as-Code Code (e.g., Terraform, CloudFormation) and modern CI/CD methodologies for seamless production environments.

Preferred

Ability to collaborate effectively with interdisciplinary research teams.
Strong system-design and analytical skills, with a focus on building resilient and well-documented architectures.
Excellent English communication skills (written and spoken)

Join our team and be part of our story!

Please note that only shortlisted candidates will be contacted.

This position will remain open until filled.

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