CTO - Distributed Systems Architect

Talent Seed United State
Relocation
This Job is No Longer Active This position is no longer accepting applications
AI Summary

Lead software team in designing and developing products, guiding distributed systems, and scaling engineering organizations.

Key Highlights
Guide software team in designing and developing products
Design and scale distributed systems
Lead large engineering organizations (200+ engineers)
Experience in complex, real-time domains
Proven success in building and deploying real-time optimization systems
Technical Skills Required
Python Go Java Microservice architectures Event-driven systems (Kafka) Geospatial frameworks (H3/S2) Machine learning infrastructure Online/offline feature pipelines Feature stores A/B experimentation platforms
Benefits & Perks
Relocation to Dubai
Flexible work environment
Entrepreneurial spirit
Strong commercial acumen
Grit
Deep appreciation for quality

Job Description


*This role requires relocation to Dubai**


Our client is looking for a CTO. In this role, you will guide the software team through the design and development of our current and future products.


You are comfortable taking action in an environment where complete information is unavailable, and you can help your team deliver well-architected products that maintain high quality. Experience coordinating many moving parts to meet tight deadlines and having contingency plans ready when priorities shift is a must-have.


We are seeking an engineering leader who has the following:

  • 15+ years of experience designing and scaling distributed, low-latency systems, including 5+ years leading large engineering organisations (200+ engineers)
  • Demonstrated expertise in complex, real-time domains such as on-demand delivery, ad-tech auctions, or high-frequency trading/energy platforms.
  • Proven success in building and deploying real-time optimisation systems — including vehicle routing, maps, dynamic assignment (e.g.Hungarian algorithm), integer linear programming, and reinforcement learning–based control loops — at 10K+ TPS scale.
  • Deep technical proficiency with microservice architectures, event-driven systems (Kafka or equivalent), geospatial frameworks (H3/S2), and languages such as Python, Go, and Java.
  • Hands-on experience establishing end-to-end ML infrastructure, including online/offline feature pipelines, feature stores and A/B experimentation platforms.
  • Relentlessly strive to push towards best practices and team goals while being flexible in a fast-paced startup environment.
  • You have an entrepreneurial spirit, strong commercial acumen, grit, and a deep appreciation for quality.

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