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Full-Stack Engineer, AI-Augmented Development & Code Intelligence

OneOrigin
Remote
Bengaluru, India· about 2 months ago

Straight from OneOrigin’s careers page. Apply on the company site — no recruiter, no middleman.

Full-Stack Engineer: AI-Augmented Development & Code Intelligence

Location: Bengaluru, India

Department: OneValue

Role Overview:

We are looking for a Full-Stack Engineer who can ship product features fast while using AI responsibly to increase velocity, quality, and consistency. This is not a role for someone who blindly accepts generated code. We need engineers who can use AI as leverage while still owning architecture, security, performance, testing, and maintainability.


You will build product features, internal tools, automation layers, code intelligence workflows, and developer experience improvements. You will also help shape how OneOrigin engineers use AI-assisted coding with discipline.


What youll own:

  • Build and ship full-stack features across React/Next.js, Node.js/Python, APIs, Postgres, and cloud services.
  • Improve internal developer workflows using AI-assisted coding, repo indexing, code intelligence, scaffolding, and PR quality gates.
  • Create internal coding copilots and repo-aware prompts aligned to OneOrigin conventions.
  • Build automation around testing, linting, CI checks, documentation, and release confidence.
  • Review AI-generated code for security, performance, edge cases, maintainability, and hidden assumptions.
  • Partner with product, design, and AI teams to turn ambiguous requirements into clean product experiences.
  • Document patterns, reusable components, and engineering playbooks.


What Success looks like:

  • Features ship faster without reducing quality.
  • AI-assisted development becomes structured, measurable, and repeatable.
  • Engineering output improves because the system helps the team work better, not because people cut corners.


You should have:

  • Strong full-stack fundamentals and production shipping experience.
  • React/Next.js, TypeScript, Node.js or Python, APIs, Postgres, and Git.
  • Solid testing discipline across unit, integration, and end-to-end scenarios where needed.
  • Ability to debug deeply and explain tradeoffs clearly.
  • Practical understanding of AI coding tools and their limitations.


Nice to Have:

MCP, internal developer platforms, monorepos, feature flags, code search, CI/CD automation, or AI code review workflows.


AI-Led Interview Focus:

You may be asked to review AI-generated code, identify risks, improve a feature design, or build a small workflow with AI assistance. We will look for engineering judgment, not just speed.

About the Company

About OneOrigin:

OneOrigin is an AI-native technology company headquartered in Scottsdale, Arizona, with a growing innovation and delivery engine in Bangalore, India. Since 2016, we have helped education institutions move from reactive operations to intelligent, proactive systems that improve enrollment, admissions, transcript evaluation, student onboarding, student support, institutional search, and operational decision-making.


Our current work is built around a connected AI ecosystem: OneAI as the intelligence foundation, Sia as the orchestration engine, OneSearch as the context and retrieval layer, and product platforms such as OneCampus, Airr, there24, OneGuide, and OneStudio. We build governed AI systems that combine agents, retrieval, automation, human review, auditability, and measurable outcomes.

At OneOrigin, AI is not a side tool. It is part of how we build, sell, support, operate, and improve.

Our AI-Led Interview Process


Our hiring process uses AI-led interviews and structured evaluations to understand how candidates think, communicate, solve problems, and use modern tools. You may be asked to complete an AI-assisted scenario, role-specific simulation, live problem-solving exercise, writing task, workflow design challenge, or technical evaluation.


AI helps us make the process more consistent and practical, but final hiring decisions are reviewed by humans. We care less about memorized answers and more about judgment, clarity, ownership, learning speed, and how well you can turn a real-world problem into a useful outcome.

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