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AI Development Toolchain Engineer
Rubiscape
Pune, IND
Full-time
Mid · 4+ years experience
Onsite
Discovered 3 weeks ago
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Role Overview
The speed at which Rubiscape ships is a product decision, not just an engineering one — and the AI Development Toolchain Engineer is the person who builds the infrastructure that makes every engineer on the platform faster. In this role, you will design, build, and operate the internal AI-assisted developer platform: the custom agents, IDE integrations, CLI tools, spec-to-code pipelines, and CI/CD hooks that encode Rubiscape’s AI-first engineering methodology into repeatable, automated workflows. You are the force multiplier behind the force multipliers — building the systems that help Rubiscape’s engineers leverage LLMs safely, consistently, and at the quality bar that Fortune 500 enterprise customers demand.
Key Skills for This Role
VS CodeCursorGitHub Copilot EnterpriseCodeiumOpenAIAnthropic
Full Job Posting
About the Role
The speed at which Rubiscape ships is a product decision, not just an engineering one — and the AI Development Toolchain Engineer is the person who builds the infrastructure that makes every engineer on the platform faster. In this role, you will design, build, and operate the internal AI-assisted developer platform: the custom agents, IDE integrations, CLI tools, spec-to-code pipelines, and CI/CD hooks that encode Rubiscape’s AI-first engineering methodology into repeatable, automated workflows. You are the force multiplier behind the force multipliers — building the systems that help Rubiscape’s engineers leverage LLMs safely, consistently, and at the quality bar that Fortune 500 enterprise customers demand.
Key Responsibilities
- · Architect and build Rubiscape’s internal AI developer platform: custom LLM agents, IDE plugins (VS Code, Cursor), CLI tools, and spec-to-code automation pipelines integrated into the engineering workflow.
- · Design and maintain the CI/CD hooks that run AI-assisted code review, spec compliance checks, and automated test generation as part of every pull request pipeline.
- · Build the infrastructure for prompt versioning, agent configuration management, and LLM call logging to ensure reproducibility and auditability of AI-generated code.
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