Simple Life App is a health coaching platform built on Next.js + React + Go, backed by a Science team across nutrition, behavior change, and digital health. The hiring mix is heavily skewed toward marketing (10 roles) and product (9 roles) with minimal engineering (2 roles), reflecting a growth-stage consumer business pivoting from product refinement to systematic user acquisition—evidenced by active projects around paid UA scaling, conversion optimization, and LTV forecasting, alongside pain points in content production velocity and onboarding friction.
Notable leadership hires: User Acquisition Head
Simple Life App delivers daily weight loss and wellness coaching through an AI coach (Avo) that provides real-time guidance without calorie counting or restrictive dieting. Founded in 2019, the company operates from London with 201–500 employees across product, marketing, design, engineering, and data functions. The product relies on evidence-based nutrition science and behavior-change principles delivered through personalized, flexible daily coaching. The company is actively scaling paid user acquisition across Meta, YouTube Shorts, and TikTok while optimizing pricing and improving lifetime-value forecasting.
Front-end: Next.js, React, TypeScript. Back-end: Go, Python, AWS (Lambda, SQS, Kinesis), Kubernetes. Data: Snowflake, Apache Airflow, dbt, Looker, Superset, Tableau. Marketing: Braze, Meta Ads, Google Ads. Design: Figma, After Effects, Adobe Premiere Pro, Runway, Midjourney, HeyGen, ElevenLabs.
Cyprus, Bulgaria, Indonesia, Armenia, United States, and Ukraine. Hiring velocity is accelerating with senior-level roles (12 open) leading the hiring mix.
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Simple Life App's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.