MojoTech

Full-stack Engineer

• Partner with the VP of Engineering to set the technical direction, team processes, and development roadmap
• Lead the architecture, development, and deployment of core platform features
• Work across the stack: React Native (mobile), Go (backend), and AWS (infrastructure)
• Own integrations with BaaS providers (e.g., Synapse, Unit, Galileo) and other fintech APIs
• Collaborate closely with product, design, and leadership to translate business needs into technical execution
• Mentor and support engineers through code reviews, guidance, and career growth
• Scale and maintain infrastructure using modern DevOps practices (IaC, CI/CD, monitoring)
• Help define and support hiring efforts to grow a world-class engineering team

Lead Engineer

• Lead client engagements across architecture, delivery, and growth
• Design and deliver scalable, maintainable systems across application, data, and AI layers
• Lead development of distributed, cloud-native applications integrating APIs, data platforms, and AI or ML components
• Ensure systems meet expectations for performance, reliability, and security
• Guide teams toward practical use of modern patterns, including microservices, CI/CD, and DevOps
• Work directly with client stakeholders to understand problems, define solutions, and align on outcomes
• Facilitate working sessions and architecture discussions with both technical and business audiences
• Build strong relationships that position MojoTech as a trusted partner
• Partner with account and sales leads to shape and win new work
• Lead delivery across one or more engagements, ensuring work stays aligned to goals, timelines, and budget
• Mentor engineers and help grow technical leadership across teams

Senior Principal Software Architect

• Design and architect scalable, resilient, and maintainable software systems across client engagements
• Lead development of complex, distributed applications integrating APIs, data services, and AI/ML components
• Design systems that incorporate data pipelines, real-time processing, and AI-driven features
• Collaborate with data engineers and data scientists to productionize machine learning models and AI workflows
• Implement architectures that support LLM integrations, RAG patterns, and intelligent automation where appropriate
• Break down complex problems into clear architectural approaches and execution strategies
• Ensure system performance, scalability, reliability, and security across application and data layers
• Guide teams in adopting modern patterns such as microservices, event-driven systems, and cloud-native architectures
• Lead technical decision-making, trade-off analysis, and system design discussions
• Drive best practices in CI/CD, DevOps, and software quality
• Mentor engineers and provide technical leadership across multiple teams
• Contribute to long-term architecture strategy, including evolution toward AI-enabled systems