Backend Engineer

We are hiring Backend Engineers to build foundational systems that support SuperApp and AI Hub. The team owns core capabilities across identity and access, workflow and job orchestration, database-backed services, APIs, billing, and revenue operations, with a focus on correctness, reliability, and maintainability in production.

Responsibilities:

• Design, build, and operate core backend systems for AI Hub, helping shape next-generation architecture and owning implementation, deployment, monitoring, and ongoing improvement.
• Own core systems spanning authentication and authorization, workflow and job orchestration, database-backed services, API layer, billing, and revenue operations.
• Design and evolve APIs, service boundaries, and data models as requirements change.
• Raise the bar on system quality by balancing scalability, reliability, maintainability, complexity, and cost while ensuring correctness and fault tolerance.
• Design clear abstractions that support extensibility and improve existing systems through testing, observability, and refactoring.
• Diagnose complex production issues, identify root causes, and implement durable fixes that prevent recurrence.
• Collaborate with engineers, product designers, and product managers to take new features and applications from ideation through implementation and into production.

Requirements:

• 1-2 years of professional software engineering experience in production-level backend systems.
• Bachelor's or master's degree in computer science, engineering, or equivalent practical systems engineering experience.
• Expert proficiency in Go and Python, with the ability to write clear, maintainable, and well-tested code.
• Deep practical understanding of concurrent programming, microservices, gRPC, and scalable API design.
• Strong understanding of distributed system design and supporting infrastructure, including message brokers such as Kafka or RabbitMQ, caching systems such as Redis, and relational and non-relational database design.
• Experience using AI-assisted development tools, with strong judgment on where they are effective, where they can fail, and how emerging capabilities can create new product and engineering opportunities.
• Ability to critically review generated code and recommendations, test them independently, and remain accountable for every change shipped.
• Understanding of enterprise production systems, including data safety, security, observability, failure recovery, performance, operational risk, and long-term maintainability.
• Experience debugging production systems and improving their reliability, performance, and operational visibility.
• Curious, collaborative, and comfortable learning as you go, with clear communication across engineering and non-engineering teams.
• Ability to navigate ambiguity, break problems into manageable milestones, seek guidance when appropriate, and bring a bias toward action, experimentation, continuous learning, and measurable outcomes.