📍
London, UK

AI Engineer Fellowship - Cogna Academy

2 years experience
Technology & Digital
Software engineering
Posted:
December 28, 2025

Cogna

AI platform for infrastructure and logistics
68
Palpable Score
Apply >view company >

Description

AI Engineer Fellowship - Cogna Academy

Location: London (hybrid).

Type: Fixed-term, 6 months, with possibility for a full-time contract afterwards based on performance.

Eligibility: Right to work in the UK.

Start date: January 1st, 2026.

We live in a world that runs on physical industries like energy, logistics, manufacturing. These sectors are essential to our economy and daily lives, yet they are held back by inefficiencies, fragile legacy systems, and decades-old ways of working. This is not just a business problem; it is a societal one. When grids fail, supply chains stall, or factories falter, entire economies are disrupted.

These companies face unique, complex challenges that typical software was never designed to solve. Cogna was founded to change this. Our mission is to give critical industries their own AI-powered Software Factory: a way to build and deploy bespoke digital tools that solve pressing operational challenges.

Since our launch in May 2023, we’ve seen incredible customer traction and revenue growth. We’re backed by leading VCs, including Notion Capital and Hoxton Ventures, and we’re building a world-class team to take on one of the most important challenges of our time.

Tackling challenges at this scale takes people who are curious, adaptable, and motivated by impact. If our mission resonates with you, we encourage you to apply, even if your experience doesn’t match every requirement. We are committed to building a diverse team that reflects the industries and societies we serve.

Why this fellowship?

The Cogna Academy is a cohort-based program for hungry, curious, hard-working builders that want to go beyond what you learned in school. The world is changing fast and LLMs open up unprecedented opportunities, but while university teaches you the theory, the Cogna Academy teaches you how to have impact and become a top-tier AI engineer.

You’ll learn faster than you’ve ever done before by shipping real complex features to production in a fast-moving high-growth startup environment, fully embedded in our world-class engineering team. Our engineers have decades of combined experience solving extremely hard technical problems in AI and software engineering and come from top teams at Palantir, Google, etc.

Apart from gaining real-world experience, you’ll also receive weekly 1:1 coaching from and pair programming directly with our co-founder, and weekly training sessions with the rest of the cohort on software engineering & AI topics.

We care less about where you studied and the theory you know, and more about what you’ve built and how fast you learn.

What you’ll do

What we’re looking for

What you’ll get

About the company

Cogna

Company overview
Cogna Educação is a large Brazilian education group with brands spanning K–12 learning solutions, publishing, tutoring and language offerings, and higher education. Cogna Educação serves schools through education systems and materials, and also serves individual learners through campuses and distance learning. Cogna Educação operates across a broad portfolio of education businesses, including large-scale school networks and education content. Cogna Educação positions the group as an education and technology company with nationwide reach.

Locations and presence

Cogna Educação operates across Brazil, with corporate hubs referenced in São Paulo state and a footprint that includes many physical higher-education units and a large distance-learning pole network. Cogna Educação roles are listed as on-site, hybrid, and remote depending on the team and city, with many vacancies distributed across multiple states.

Palpable Score

68
/ 100
Cogna Educação offers real entry points through named internship and trainee routes plus a steady volume of junior vacancies on the main job board. Hiring steps and benefits are often spelled out clearly inside individual postings, but candidate experience signals are uneven and salary ranges are not consistently shown. Outcomes are hard to judge at scale because public materials highlight a few program results but do not publish wider early-career retention or progression metrics.
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