Crypto Pro
Senior Backend Engineer (Sports & Prediction Markets) – Golang
United States · Senior
Sponsorship not specified$130k-$160kDetected 37 days ago
GoDistributed SystemsBackend DevelopmentCode ReviewPostgreSQLRedisKafkaStakeholder ManagementRecruitingCommunicationCollaboration
About the role
- We are seeking a highly skilled Mid-to-Senior Backend Engineer to spearhead the growth of our 24/7 high-throughput infrastructure, with a particular focus on expanding our core domains into the sports, prediction ecosystem.
Responsibilities
- Design, develop, and optimize robust, highly scalable backend services and distributed systems in Golang to power our 24/7 global trading and sports-domain applications.
- Develop backend services and operations, including proposing architectural decisions, participating in design reviews, coding, code review, and implementing features
- Act as the technical subject matter expert to increase and embed deep sports domain knowledge into our core backend, building features tailored to prediction markets, real-time sports data feeds, and interactive mechanics.
- Operational Support: Provide high-tier technical operational support to address complex, real-time client issues and maintain flawless systemic availability.
- Provide high-tier technical operational support to address complex, real-time client issues and maintain flawless systemic availability.
Requirements
- Solid mid-to-senior level professional experience specializing in backend system development, with an absolute proficiency and production-level mastery.
- Proven experience working closely with Sports systems, Sportsbooks, Prediction markets, or high-velocity sports-data infrastructure.
- Proficiency in Golang, Postgres, Redis, and Kafka preferred
Nice to have
- Deep familiarity with transaction-heavy, money-related modules, or payment ledgers.
- Advanced expertise in designing complex concurrent systems, race-condition mitigation, and distributed state machines.
- Previous professional experience operating smoothly within a rapid, ambiguous, or highly entrepreneurial startup environment.
- Life @ Crypto.com Empowered to think big.
- Try new opportunities while working with a talented, ambitious and supportive team.
- Transformational and proactive working environment.
- Empower employees to find thoughtful and innovative solutions.
- Growth from within.
Compensation
- Benefits Competitive salary Attractive annual leave entitlement including: birthday, work anniversary 401(k) plan with employer match Eligible for company-sponsored group health, dental, vision, and life/disability insurance Work Flexibilit
Benefits
- Attractive annual leave entitlement including:
- birthday, work anniversary 401(k) plan with employer match Eligible for company-sponsored group health, dental, vision, and life/disability insurance Work Flexibility Adoption.
- Our Crypto.com benefits packages vary depending on region requirements, you can learn more from our talent acquisition team.
Company info
- ABOUT THE ROLE We are seeking a highly skilled Mid-to-Senior Backend Engineer to spearhead the growth of our 24/7 high-throughput infrastructure, with a particular focus on expanding our core domains into the sports, prediction ecosystem.
- This role demands an engineer who thrives within a fast-paced, startup-minded ecosystem, possessing a deep domain understanding of sports platforms / prediction environments, and capable of keeping critical transactional networks running flawlessly around the clock.
- About Crypto.com: Founded in 2016, Crypto.com serves more than 150 million customers and is the world's fastest growing global cryptocurrency platform.
- Crypto.com is an equal opportunities employer and we are committed to creating an environment where opportunities are presented to everyone in a fair and transparent way.
Equal opportunity
- Crypto.com values diversity and inclusion, seeking candidates with a variety of backgrounds, perspectives, and skills that complement and strengthen our team.
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This listing is sourced directly from Crypto Pro's careers page and normalized into a canonical job model.