Freelance Senior Technical Advisor

About this role

Role Details Level : Senior/ Lead Start Date : ASAP Duration : 6 months Day Rate : Dependent on experience Weekly hours : 3-4 days/ week Location : Remote Europe, GMT/BST or CET friendly Language : English, plus Spanish and/or Portuguese In this role, you’ll be a senior technical advisor to city governments across North, Central and South America, working in both an advisory and a hands-on capacity to help them design, build and launch small scale pilots of new services for residents.

Working alongside experienced product managers, data scientists, AI engineers, and designers, you’ll help multidisciplinary city teams build in-house product development capability by prototyping and delivering digital products and services, many of which harness data and AI. You won’t own the decisions, but you’ll shape them. You’ll guide cities through the full product development lifecycle, helping them weigh the strategic and technical trade-offs at each stage: how to design system and data architecture that’s right-sized for a pilot but built to scale, how to prototype and test possible solutions to validate assumptions, and when AI approaches such as machine learning or large language models are the right tool (and when they aren’t).

You’ll roll up your sleeves to prototype and demonstrate what good looks like, while making sure your clients understand the reasoning well enough to own the outcome. This role suits someone with the technical depth of a tech lead, and the judgement, communication skills and patience to lead through influence rather than authority. You’ll need to work fluently in English and in at least one of Spanish or Portuguese. Key skills and experiences Extensive hands-on technical experience, with strong knowledge of system and data architecture, data pipelines, DevOps and infrastructure, and a track record of delivering and deploying robust solutions end to end, from prototype to pilot, across cloud, on-premises and hybrid environments, including legacy systems and resource-constrained ones, so that your recommendations are realistic and buildable.

Familiarity with AI and machine learning approaches, including large language models, and experience deploying them or working alongside ML engineers to integrate them into products, with enough understanding to judge when they’re the right tool and how to build them in responsibly. Experience taking products from early concept to first release, while laying foundations for scale, with a track record of rapid prototyping and assumption testing and a “show, don’t tell” approach that uses working prototypes to build shared understanding and inform decisions.