Founding Engineer

City of London
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer

Lead Data Scientist

Data Scientist

Lead Data Scientist

AI/Data Scientist

Research Assistant/Associate in Data Science and Computational Neuroscience

Founding Engineer

About Them:

They're a mission-driven company developing a revolutionary mobile app to enhance the quality of life for individuals living with cognitive conditions and their support networks. Their platform provides essential tools like live location tracking and alerts, alongside a shared calendar to coordinate care among family members, healthcare providers, and other support partners. Leveraging behavioral recognition and machine learning, their app adapts to each user's unique habits, delivering personalized support that fosters greater independence and peace of mind.

Who You Are:

Technical Expertise: You bring robust software engineering experience, ideally with full-stack capabilities, and have successfully built and launched products in agile environments.
Proficiency Across Tech Stack: You're comfortable with technologies such as:
Front-end frameworks: React, Angular, Flutter, Vue.js, etc.
Back-end development: TypeScript, Node.js, Python, Ruby, and more
Cloud providers: AWS, Google Cloud, Azure
Databases: SQL and NoSQL
Mobile development: iOS and Android
Machine Learning Experience: Practical experience building machine learning models; familiarity with location-based or healthcare data is a bonus.
Startup Mentality: You thrive in fast-paced, dynamic environments and enjoy the challenges of a startup setting.
Leadership: Previous experience mentoring or leading small teams, and an interest in developing the technical side of the business from the ground up.
Passion for Healthcare Innovation: A deep interest in advancing healthcare technology and patient-centric solutions, especially for those with cognitive conditions.Bonus Skills:

Experience building healthcare apps, EHR, or patient management systems
Familiarity with data security standards like HIPAA
Knowledge of UX/UI design principles for healthcare
Experience with wearable and mobile sensor integration

Role Overview:

In this key technical role, you'll be instrumental in shaping and growing the platform that supports people with cognitive conditions and their care teams. You will:

Drive Product Development: Enhance their core software (app/web platform) to meet the evolving needs of users, caregivers, and healthcare providers.
Collaborate with Founders: Align technical development with the broader business vision and user needs alongside their founding team.
Hands-on Development: Write high-quality, scalable code, contributing across the full stack.
Define Tech Strategy: Establish the platform's architecture, selecting the right tools for development, deployment, and scaling.
User-Centric Design: Design for accessibility and ease of use, ensuring an intuitive experience for users with cognitive conditions and their caregivers.
Ensure Compliance and Security: Uphold industry standards, including GDPR, HIPAA, and secure handling of data.
Scale for Growth: Build a resilient platform that can scale with their user base and adapt to shifting healthcare requirements.
Team Development: As they grow, help recruit and lead a talented tech team, including developers, data scientists, and engineers.
Continuous Product Improvement: Drive updates and enhancements based on user feedback and emerging trends in healthcare technology.If you're passionate about healthcare and excited to use technology to make a meaningful impact, this role offers a unique opportunity to be part of something transformative

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.