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Software Engineer Intern

RELIXIR

Updated on: 26 October 2025

Additional Details

Website

relixir.ai

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Work Location

New Delhi, India (Hybrid / Remote flexibility)

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Job Type

Internship + FTE

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Batch

2027 |2026| 2025

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Stream Required

B.E / BTech. / MTech. / M.E (CSE , or a related field)

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Salary

30K - 70K per month (Stipend)

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Job Description

🧠 Role: Software Engineer Intern (Full-Stack / Backend / AI Infra)

 

Location: New Delhi, India (Hybrid / Remote flexibility)

Duration: 3–6 months (extension or full-time offer possible)

Stipend: Competitive (₹30,000–₹70,000/month depending on skill and contribution)

 

🌍 What You’ll Work On

 

Build and scale AI-driven analytics systems that simulate real-world search behavior across ChatGPT, Perplexity, and Google.

 

Develop and optimize backend APIs (Python / FastAPI / Supabase / PostgreSQL).

 

Contribute to our Next.js-based dashboard for enterprise analytics and visualizations.

 

Integrate with LLMs, embeddings, and vector search pipelines to measure search visibility.

 

Work with a tight, high-velocity team of YC founders and engineers shipping product weekly.

 

🧩 You’re a Great Fit If You

 

Are fluent in Python, JavaScript/TypeScript, and familiar with React / Next.js.

 

Understand APIs, queues, and modern cloud infra (AWS / Vercel / Supabase / Fargate).

 

Love working on fast-moving early-stage products and learning across the stack.

 

Have curiosity about AI, SEO, or search analytics.

 

Are self-driven — you like solving hard problems independently and shipping fast.

 

💡 Bonus Points For

 

Experience with LLM APIs (OpenAI, Anthropic, etc.)

Interest in data visualization, analytics, or agentic AI systems

Past work on side projects, open source, or startup internships

 

Why Join Relixir

  • Work directly with founders from Y Combinator who’ve scaled AI infrastructure to millions of searches/day.
  • Get exposure to cutting-edge work in AI search, visibility analytics, and data infra.
  • Contribute meaningfully — your code will ship to real enterprise users.
  • Learn startup execution from 0→1 in a high-trust, fast-iteration environment.

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