Engineering Lead – AI for Knowledge Hub

About the role

The United Nations Human Settlements Programme (UN‑Habitat) is seeking an Engineering Lead to drive the AI for Knowledge Initiative. This 6‑month consultancy will establish a production‑grade AI platform that UN‑Habitat staff can use globally and lay the foundation for future public release.

Key responsibilities

• Define the technical roadmap together with the ML Lead and Team Lead, aligning infrastructure decisions with product goals and UN‑Habitat’s mission.
• Act as the primary technical liaison for partners and stakeholders, translating product requirements into scalable infrastructure solutions.
• Design a secure, scalable architecture for internal deployment across Country Offices and future public availability.
• Set up engineering standards, CI/CD pipelines, and infrastructure‑as‑code environments for reliable dev/test/prod workflows.
• Develop and maintain backend APIs and services that enable analytical execution and dataset access.
• Implement comprehensive security controls, including authentication, authorization, role‑based access, and secret management.
• Ensure platform reliability through monitoring, logging, backup, recovery, and performance management.
• Create and keep up‑to‑date technical documentation, architecture diagrams, and runbooks.
• Mentor new team members and build engineering capacity as the initiative scales.

Required profile

• Advanced university degree (Master’s or equivalent) in Computer Science, Software Engineering, Data Engineering, Information Systems, Physics, Mathematics or a related quantitative field.
• Proven experience leading complex engineering projects, preferably in AI or data‑intensive platforms.
• Strong understanding of cloud infrastructure, DevOps practices, and secure software development.

Required skills

• CI/CD pipeline design and implementation
• Infrastructure‑as‑Code (e.g., Terraform, CloudFormation)
• Backend API development
• Security and access‑control mechanisms
• Monitoring, logging, and performance management