MOJO is looking to hire a senior engineering leader to help scale the next phase of its prediction markets and trading infrastructure platform.
The business operates at the intersection of trading, quantitative research, market making, and prediction markets, with a growing focus on scalable execution systems, real time data infrastructure, and future facing Ai driven tooling.
This is a broad technical leadership mandate rather than a purely specialist low latency engineering role. The team is looking for someone who understands how production trading environments operate end to end across execution, market data, risk systems, and scalable infrastructure.
The ideal profile is likely someone currently operating at VP, Director, or senior engineering leadership level within a bank, trading firm, market maker, or proprietary trading environment, with hands on experience building and scaling trading technology platforms.
Responsibilities
• Lead and scale MOJO’s trading technology infrastructure across prediction markets and multi asset trading systems
• Oversee execution services, market data systems, and risk infrastructure operating in live production environments
• Partner closely with traders and quantitative researchers to improve execution quality, platform scalability, and system reliability
• Help shape the long term architecture of the business across low latency systems, Ai tooling, and modern data engineering workflows
• Direct engineering efforts across Python, C++, Golang, AWS, and distributed trading infrastructure
• Build scalable infrastructure capable of supporting increasing trading volumes and new market initiatives
• Mentor and grow a high calibre engineering team while remaining involved in architecture and technical strategy
• Work directly with senior leadership on long term platform scalability and future technology direction
Desired Background
• Strong experience within trading technology environments, ideally from banks, proprietary trading firms, market makers, exchanges, or electronic trading platforms
• Broad understanding of trading systems, execution infrastructure, market data platforms, and real time risk systems
• Experience operating within low latency or performance sensitive trading environments
• Strong technical knowledge across Python environments, with exposure to C++ and/or Golang systems
• Experience with AWS based cloud infrastructure and scalable distributed systems
• Familiarity with Ai tooling, machine learning infrastructure, and modern data engineering environments
• Multi asset trading exposure across equities, futures, options, crypto, or electronic markets
• Strong understanding of how live production trading systems operate at scale
• Ability to operate strategically while remaining technically credible and hands on when required
Compensation
• Base compensation targeted around $250k to $300k
• Equity participation
• Profit share structure
• Significant long term upside tied to the growth of the platform and prediction markets ecosystem
