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India-based · Remote · 6 months · Immediate start preferred

About LingocareLingocare is a next-generation language and skills training platform helping nursing and healthcare students master skilled German through interactive scenarios, AI-driven feedback, and real-world simulations. We're on a mission to make learning engaging, personalized, and impactful.

The Role

This is not a ticket-execution role. You'll work with pedagogical experts, nursing instructors, care workers, and students, and your job is to figure out what the actual problem is before deciding what to build. Then you'll build it across the full stack: Express APIs, MongoDB, Next.js, React, and a meaningful chunk of AI work including Claude integrations, RAG pipelines, and safety guardrails.

About 40% of your work touches AI directly. But the part that separates good work from great work here is the other 60%. Complex domain, real user feedback, no tolerance for unnecessary clicks and complex apps.

What You'll Work On

- Ask Lingo: wire the AI assistant into instructor and learner dashboards, handle streaming responses, improve retrieval accuracy.
- Magic Write: AI-assisted content creation for exercises and knowledge blocks, prompt engineering, output validation.
- RAG system: embed curriculum content, build retrieval pipelines, evaluate answer quality.
- Safety layer: implement AI guidelines (no medical diagnoses, no ethical violations), build validation systems that enforce them.
- Dashboards and admin: progress visualization, alert systems, user management, school onboarding.

What We're Looking For

You think about the person before the feature: You've used Notion, Linear, Google AI Studio, or similar tools long enough to have actual opinions about them. You know why they feel effortless. You've looked at a bad enterprise tool and been able to name exactly what's wrong with it.



When you're handed a spec, your first question is not "how do I build this" but "does this make the person's life simpler, or am I just moving complexity around."

You've shipped something real: A side project counts. But there has to be something you can show and explain, not just code that runs locally. More importantly, you should be able to talk about the user feedback you got and what you changed because of it.

You've called an LLM in code: Not just used Claude in the terminal. You've written a prompt, handled the response, and dealt with the moment it returned something wrong. You know what tokens cost.

Technical foundations: TypeScript or JavaScript, React or Next.js, Node.js or Express, REST APIs, MongoDB or SQL. You don't need all of these. You need solid ground in at least one area and the ability to learn the rest.

For the AI side: understand prompt engineering basics, know what RAG is and why you'd use it, have thought about what to do when an LLM hallucinates. The AI work here is not optional and not introductory.

Mindset:

- You push back when a design decision makes the user's job harder, even if nobody asked you to.
- You can take a vague idea from a domain expert, a few conversations with real users, and no detailed brief, and turn it into a working feature you can defend.
- You care that the AI output is correct, not just plausible. In a healthcare education context, those are very different things.
- Complexity in the codebase is sometimes unavoidable. Complexity in the interface never is.





Don't Apply If

- You've never shipped or deployed anything a real person used
- You've never questioned whether a feature in a spec should exist
- You've never worked with an LLM in code. If that's you, spend a week building something small with the Claude API first, then apply.
- You're looking for a job of turning figma design into pages. If thinking about user workflows sounds like extra work rather than the actual job, don't apply.

What you get

1. You work closely with a senior engineer on high-stakes development.
2. Real client work in your portfolio. Lingocare is supported by the Hessen Government, Germany, pitching an EU-market startup, seen by real stakeholders.
3. Direct access to founders.
4. You'll sit with experts who've spent decades in nursing and pedagogy studying how learning happens under pressure and exhaustion — domain depth and direct user feedback most engineers never get close to.
5. Real exposure to German nursing education: its curriculum, its clinical language, and why trainees actually drop out.
6. The full build lifecycle, from a rough conversation to a feature shipped and used by real classrooms. AI used in production, not demos.
7. We hire very few interns because we want them to become full-time employees.
8. Stipend starts at ₹15,000/month, moving up based on performance across the rounds.
9. You're treated as the expert in your field from day one. You make calls with strong reasoning.
10. Flexible working hours (mostly in CEST), with respecting commitments as first priority.
11. We grow as a team and believe in sharing success together with everyone who contributed.

The Process

1. Apply
2. Technical Task
3. Technical Deep Dive
4. Conversation
5. Offer

Thank you for reading this far! The chances are already high now :)

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📌 Full Stack Developer Intern (India)
🏢 lingocare
📍 India