Founding Product Engineer — Venture Platform & Infrastructure
The Studio
| Company | The Studio |
| Category | Engineering |
| Location | Doha |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 80k–120k |
| Posted | 12 Nov 2025 |
| Last verified | 7 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
ABOUT THE STUDIO
Utopia Studio is an AI-native venture builder for the Global South, backed by Qatar Development Bank. We work with domain experts across the GCC, Southeast Asia, and Africa to accelerate venture creation through AI-driven execution and shared infrastructure.
At the core is Utopia OS — a modular platform that automates what's repeatable, embeds AI agents across workflows, and lets learning compound across ventures.
ABOUT THE ROLE
We're looking for a founding product engineer to build the platform and infrastructure side of Utopia OS. You’ll design, develop, and scale the shared systems, data pipelines, and full-stack applications that power dozens of AI-native ventures launching from Doha for the Global South.
You’ll combine deep backend expertise with the ability to deliver seamless, data-driven web experiences that make AI-native venture building faster and smarter.
You will work as part of a product trio with the Design Lead and the Rapid Prototyping Engineer, making joint decisions on discovery, scope, and technical approach.
Reports to: Studio Director
Growth path: Head of AI Platform / CTO track
RESPONSIBILITIES
PLATFORM ENGINEERING & INFRASTRUCTURE
- Architect, build, and maintain Utopia OS infrastructure: auth, data systems, deployment, monitoring, analytics
- Develop full-stack web apps and plugins for studio-wide decisioning and analytics
- Build and maintain data pipelines for ingestion, transformation, and deployment across all ventures
- Develop and maintain robust backend systems and APIs, integrating modern databases (Postgres, Supabase, PlanetScale) and data architectures (Iceberg, Delta Lake).
- Implement data pipelines and transformation workflows (Dagster, Airflow) to enable real-time analytics across ventures.
- Create clear, reusable documentation and internal tooling to standardize engineering practices across the platform.
- Take early-stage products and harden them for scale, reliability, and compliance.
- Collaborate with design and product teams to translate data and infrastructure capabilities into intuitive user experiences and venture-facing tools.
- Implement CI/CD, observability, and security frameworks across the portfolio
- Design deployment templates for multi-tenant environments and enterprise integrations
COLLABORATION & ENGINEERING EXCELLENCE
- Work closely with venture teams to integrate AI workflows and shared infrastructure
- Improve developer experience through modern, intuitive tool design
- Provide technical guidance and mentorship to engineers and fellows — fostering a culture of learning, experimentation, and shared standards across the Studio.
- Document architecture, standards, and playbooks so they can be reused across the studio
- Communicate complex technical concepts clearly to both engineering and non-technical stakeholders — turning systems thinking into shared understanding.
- Stay current with advances in generative AI, data infrastructure, and modern web engineering
- Work in a tight loop with the Design Lead on design system needs and with the Rapid Prototyping Engineer to productionize validated prototypes into secure, scalable services.
- Co-own technical discovery with the product trio: define evaluation plans, success metrics, and risks before committing to builds.
- You’ll also help the team build shared capabilities typically owned by dedicated functions — like LLMOps, Data Engineering, and Security — but in a lean, integrated way.
- That means establishing lightweight evaluation pipelines, data ingestion templates, and security practices that can scale across multiple ventures without extra overhead.
- These foundations will later evolve into formalized systems as Utopia grows.
- We operate as a compact, AI-native core team — covering product, design, and engineering end-to-end.
- Each of us contributes to early foundations in areas like evaluation, data, re