Role Summary

We are hiring a Senior Software Engineer to help build the future of technical interviewing and assessment across CoderPad.

This is a fullstack role for someone who can move across backend services, frontend product surfaces, and AI-powered system design. You will work on user-facing features, production infrastructure, and internal engineering workflows where coding agents and AI-assisted development are part of normal day-to-day execution.

This role is remote from Latin America.

What You Will Work On

• Build and ship fullstack product features across candidate and recruiter experiences, from API and data model design to frontend implementation.
• Improve real-time AI-powered experiences used in interviews and assessments, including model orchestration, streaming UX, tool/function-calling patterns, and reliability.
• Contribute to systems that integrate multiple LLM providers and require pragmatic handling of latency, cost, observability, and non-deterministic behavior.
• Develop and improve deterministic internal tooling that helps engineers and agents execute work safely, repeatably, and with strong audibility.
• Partner across product, design, and platform teams to take ambiguous problems from definition to production rollout.
• Lead and mentor through code review, using reviews as both a quality gate and a coaching channel for less-experienced engineers.
• Plan and deliver technical debt, architecture, and observability initiatives that improve long-term system maintainability.
• Participate in on-call operations and drive runbook, reliability, and incident follow-up improvements.

Requirements

• Senior-level experience shipping production software end-to-end in a fullstack capacity.
• Strong backend engineering skills in at least one modern language and ecosystem, plus practical frontend experience with a component-based framework.
• Proven ability to pick up unfamiliar stacks quickly and deliver in mixed-technology environments.
• Hands-on experience with agentic development workflows (for example: Cursor, Claude Code, Codex, or equivalent), including good judgment on delegation, context scoping, and review of AI-generated code.
• Experience building production systems that use AI, such as LLM API integrations, prompt and context design, streaming responses, tool/function calling, and token or cost-aware engineering.