You will build and maintain fullstack product features while integrating AI-powered experiences and LLM providers into the platform. Additionally, you will lead technical initiatives, mentor junior engineers, and ensure the reliability and observability of production systems.
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.
- Significant contribution to code review, with evidence of raising code quality and mentoring peers through the review process.
- Experience identifying and reducing technical debt, and contributing to architecture planning and documentation.
- Proven ownership of production system health through monitoring/alerting improvements, incident response, and operational follow-through.
- Experience partnering with product and technical leads on backlog preparation, scoping, sizing, and delivery planning.
- Strong engineering fundamentals in testing, observability, debugging, and safe incremental delivery.
- Clear written communication and collaborative ownership mindset in remote teams.
Desired Stack
You are not expected to know all of these technologies. Relevant equivalent experience is absolutely welcome.
- Backend surfaces include Ruby on Rails, Java services, and Node/TypeScript services.
- Frontend surfaces include React + TypeScript applications and shared web platform tooling.
- AI systems include integrations across Anthropic, OpenAI, Gemini, Llama, and Mistral families, with streaming and tool-calling capabilities.
- Platform and infrastructure include PostgreSQL, GraphQL, Redis/Sidekiq, Firebase Realtime Database, Datadog, LaunchDarkly, GitLab CI, cloud services (AWS and GCP), and containerized execution environments.
- Internal engineering workflows include Python-based deterministic CLI tooling and AI-agent skills that support repeatable development operations.
How We Work
- Remote-first collaboration across time zones with a strong written culture.
- AI tooling is an expectation and treated as part of the engineering toolbox.
- Small, reviewable changes with high-quality code review and shared ownership of outcomes.
- Pragmatic architecture decisions focused on reliability, maintainability, and user impact.
- Documentation and operational clarity are part of shipping, not afterthoughts.
- Senior ICs influence technical roadmap direction beyond their immediate delivery scope.
- Operational ownership matters: we value engineers who improve on-call practices and close the loop after incidents.
Logistics
- Required overlap window with core team: Pacific 7:00 - 16:00, on-call 24 hrs for a week once every 8 weeks or so.
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