Role Overview
We are looking for a Full Stack Engineer to work across frontend, backend, APIs, databases, data workflows, and AI/ML-enabled features. You will help build and maintain systems that process data from raw inputs into structured, reviewed, and decision-ready insights.
We are actively seeking female candidates for this role.
Key Responsibilities
Full Stack Development
Develop and maintain responsive frontend interfaces using Angular
Build reusable components, services, and modules supporting dashboards, review workflows, and partner-facing features
Design, build, and maintain backend services and RESTful APIs
Work with relational databases to support structured data storage, filtering, reporting, and analytics
Debug issues across frontend, backend, APIs, databases, background jobs, and deployment environments
Data Workflows
Build and improve workflows for ingesting and processing data from multiple input channels
Support data processing pipelines that transform raw submissions into structured records
Implement metadata capture, validation rules, status tracking, review queues, and audit trails
Support dashboards for viewing, filtering, analysing, and exporting data
AI/ML Integration
Integrate AI and machine learning outputs into workflows, including classification, tagging, summarisation, clustering, and signal detection
Support model inference pipelines through APIs, backend services, or batch processing
Work with confidence scores, model outputs, error handling, fallback rules, and human review processes
Support preparation of datasets for model fine-tuning — cleaning, labelling, formatting, and quality checks
Build human-in-the-loop workflows ensuring sensitive or uncertain AI outputs are reviewed before reaching end users
Qualifications
5+ years of professional full-stack development experience
Experience with Angular for frontend development
Experience with PHP and frameworks like Laravel or Symfony
Experience with Node.js for building APIs and microservices
Experience with AI/ML integration — model outputs, inference pipelines, or dataset preparation
Strong experience with relational databases (MySQL/PostgreSQL)
Experience building dashboards, admin tools, or data-driven web applications
Experience with Git
Knowledge of Docker, Kubernetes, or similar containerisation technologies is a plus
Experience with GIS, preferably Leaflet, is a plus
