Moniepoint - Principal Generalist Engineer
Requirements
• Strong CS fundamentals (DSA, OS, networking, distributed systems) • Solid probability and statistics • Experience building production systems at scale • Ability to move across languages (Go, Java, Python, Rust, SQL) • Understanding of system behavior under load and failure • Comfort with Linux, containers, Kubernetes • Strong debugging skills • Ability to reason using invariants and failure modes • Data systems, streaming systems, ML infrastructure, performance optimization • What We Value • Ownership over problems • Simplicity over complexity • Curiosity about internals • Robust design thinking • Clear communication • What Success Looks Like • Deliver working production systems from ambiguous problems • Build reliable, scalable systems • Reduce complexity • Earn trust in technical judgment • If you are a builder, a systems thinker, and a technologist who loves exploring what’s next, we’d love to have you help shape the future of Moniepoint. • What we can offer you • Culture - We put our people first and prioritize the well-being of every team member. We’ve built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human. • Learning - We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks. • Compensation - You’ll receive an attractive salary, pension, health insurance, paid leave plus other benefits. • What to expect in the hiring process • Our interview process is designed to be thoughtful, transparent, and candidate-friendly, allowing you to showcase your strengths while getting to know us better: • Initial Conversation: A brief introductory call with our recruiter to learn more about your background, career goals, and to share insights about the role and our team. • Technical Assessment: A practical, take-home assessment follow by a discussion with an interviewer on a call. • System Design Interview: A focused session with our Engineering Team, where we'll explore system design, architecture, and problem-solving approaches. • Final Interview: A combined technical and behavioural conversation with a member of our Executive Team, aimed at understanding your alignment with our values, vision, and culture
Responsibilities
• Design and build production-grade systems that are reliable, scalable, and observable. • Own systems end-to-end: problem → design → data → implementation → deployment → operations. • Work across application services, distributed systems, infrastructure, data pipelines, and ML systems • Debug complex production issues across multiple layers • Make engineering trade-offs grounded in first principles • Improve performance, latency, reliability, and cost efficiency • Contribute to architecture and technical direction • Write maintainable code and documentation • Raise the engineering bar • Frame problems correctly: when to use ML vs deterministic systems • Work with data end-to-end • Train, evaluate, and iterate on models • Build reproducible pipelines • Deploy models and monitor performance, drift, and cost • Debug system + model failures
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