About the project
The AI Risk Explorer (AIRE) is an online platform that monitors large-scale AI risks across four domains: cyber offense, biological risk, loss of control, and manipulation. AIRE produces structured datasets and analytical intelligence to support policymakers, researchers, practitioners, and journalists working on frontier AI risk. Our work surfaces underreported evidence and aggregates data to identify emerging risk patterns.
About the role
As a Full-Stack Software Engineer, you will be instrumental in maintaining and expanding AIRE's technical infrastructure, which encompasses our public website, content management system, data pipelines, and semi-automated workflows.
This role is vital for building scalable systems that ensure the seamless operation of our monitoring, analysis, and dissemination efforts as we scale.
You will collaborate closely with another full-stack engineer within a lean, two-person team. While the exact division of responsibilities will be tailored to your expertise and seniority, we have a slight preference for a full-stack engineer with a strong front-end focus.
The responsibilities and requirements below cover a wide range of engineering needs that we don't expect a single engineer to cover. We expect that most strong candidates will not fulfill all requirements, and that the final hire will work on a subset of the listed responsibilities. However, we want to preserve flexibility in how we structure the team: depending on the hire's strengths, we may prioritise different workstreams or redistribute responsibilities between the two engineers accordingly. If your background covers some but not all of the areas below, we still encourage you to apply.
Responsibilities
- Web & Front-End Engineering. Develop and expand the public AIRE website, incorporating interactive dashboards, informational explainers, and databases. Responsibilities include optimizing existing features, introducing new functionalities, maintaining brand consistency, maximizing performance, and implementing SEO best practices for a seamless UX.
- Content Management System. Support and upgrade the internal administrative interface, empowering non-technical personnel to independently author, evaluate, and publish structured content across all AIRE platforms without needing direct support from the engineering team.
- Data Pipeline Infrastructure. Manage and scale a semi-automated pipeline designed to discover, screen, and process materials connected to AI risk. This entails handling automated ingestion from feeds like Google Alerts, arXiv, and RSS, triaging data by origin and target destination, deduplicating records, and improving an LLM-driven routing framework to deliver structured outputs.
- Database Administration. Oversee the core data layer for AIRE, which includes managing backend architectures and schema configurations for major entities such as companies and models. Additionally, build on the current vector embedding systems to facilitate semantic search across the entire document repository.
- Workflow Automation. Design, implement, and maintain semi-automated processes aimed at minimizing manual administrative overhead throughout the intelligence cycle, including operations like stakeholder engagement tracking.
Requirements
Required
- 5+ years of professional software engineering experience with a demonstrable track record of architecting, developing, and deploying complex software systems in production environments.
- Strong proficiency in modern front-end engineering stacks, specifically React JS, Next.js, and Tailwind CSS, with experience building high-performance public websites, interactive dashboards, maps, and internal administrative interfaces.
- Solid experience working with modern testing frameworks in JavaScript to guarantee infrastructure reliability, maintain high code quality, and ensure seamless user experiences.
- Strong familiarity with backend technologies, particularly Node.js and Docker, to build, maintain, and expand scalable, semi-automated content workflows and data pipelines.
- Extensive experience managing relational databases, specifically Postgres and platforms like Supabase, including database schema design for core platform entities and implementing vector embedding infrastructure.
- Hands-on familiarity with LLM APIs and proven experience building LLM-powered workflows, custom routing layers, or RAG-enabled tools to assist in intelligent data processing.
- Comfort designing and working with web scraping utilities, RSS ingestion protocols, and third-party APIs to manage automated collections from diverse platforms like Google Alerts, arXiv, X, and Reddit.
- Practical knowledge of cloud infrastructure management, specifically within Google Cloud Platform (GCP), alongside modern containerization strategies to support continuous integration and deployment.
- Excellent written and verbal communication skills, with a focus on documenting technical architectures clearly and maintaining readable records for a non-technical internal team.
- Ability to execute work independently and maintain proactive ownership within an agile, early-stage setting defined by high ambiguity, shifting requirements, and a lean engineering team.
Nice to have
- Experience with vector databases or RAG architecture (pgvector, Pinecone, or similar).
- Familiarity with D3.js or other data visualization libraries.
- Experience with Supabase, n8n, Airtable, and other no-code/low-code automation tools.
- Interest in and familiarity with AI safety, since AIRE's work will be more legible to engineers who follow the field.
- Some familiarity with Python for data processing.
Working with the team
You'll collaborate closely with another full-stack engineer in a lean, two-person team, reporting to the Project Director. Working hours are generally flexible, with an expectation of at least two hours of daily overlap with the team's core collaboration hours (UTC+2 / UTC+3, depending on daylight saving time). The role includes a weekly one-on-one with your supervisor and a weekly team alignment meeting; outside of these, work is performed asynchronously.
Contract type
The selected candidate will receive a 2-month independent contractor agreement. Subject to satisfactory performance, project needs, funding availability, and mutual agreement, this is expected to be followed by a 6-month agreement, with subsequent renewals depending on project needs.
Application process
- 1Submit your application by completing the online application form.
- 2Applications will be reviewed and shortlisted candidates invited to a paid work test.
- 3Final interview with members of the AIRE team.
- 4Engagement offer for the selected candidate, outlining the key engagement terms.
Only shortlisted candidates will be contacted. We aim to keep candidates informed throughout the recruitment process.
Questions?
Contact info@airiskexplorer.com with any questions about the role or the process.