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AI-Augmented Software Engineer
Rubiscape
Pune, IND
Full-time
Mid · 3+ years experience
Onsite
Discovered 3 weeks ago
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Free
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Role Overview
At Rubiscape, software engineering is being reimagined from the ground up. As an AI-Augmented Software Engineer, you will work at the frontier of AI-assisted development, using LLM-powered pair-programming, spec-driven workflows, and intelligent code review tools to ship production-grade features across our six-studio Decision Intelligence Platform at speeds previously impossible. You will help establish the engineering culture and toolchain patterns that allow Rubiscape to deliver 3× faster pipelines and <90-day production use cases to Fortune 500 customers. This is not a role for prompt-curious hobbyists — it is for engineers who see AI as a force multiplier and want to build the systems that India’s enterprises run on.
Key Skills for This Role
PythonTypeScriptJavaGitHub CopilotCursorLangChain
Full Job Posting
About the Role
At Rubiscape, software engineering is being reimagined from the ground up. As an AI-Augmented Software Engineer, you will work at the frontier of AI-assisted development, using LLM-powered pair-programming, spec-driven workflows, and intelligent code review tools to ship production-grade features across our six-studio Decision Intelligence Platform at speeds previously impossible. You will help establish the engineering culture and toolchain patterns that allow Rubiscape to deliver 3× faster pipelines and <90-day production use cases to Fortune 500 customers. This is not a role for prompt-curious hobbyists — it is for engineers who see AI as a force multiplier and want to build the systems that India’s enterprises run on.
Key Responsibilities
- · Design and implement features across RubiFlow, RubiStudio, RubiSight, and RubiAI studios using an AI-first, spec-driven development workflow.
- · Pair with GitHub Copilot, Cursor, and custom internal LLM agents to accelerate code generation, refactoring, and test coverage without sacrificing code quality.
- · Translate structured functional specs into implementation plans, breaking ambiguous requirements into verifiable, AI-executable tasks.
- · Participate in AI-assisted code review cycles: generating review prompts, interpreting LLM feedback, and validating AI suggestions against platform architecture standards.
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