Job Title: Founding Full-Stack Engineer (AI-Native)

Location: Remote

Employment Type: Full-Time, Permanent

Working Days: Monday to Saturday

Salary: 24LPA to 60 LPA

Read this first

This is not a maintenance role. Were not looking for someone to pick up tickets from a backlog and close them at a comfortable pace. Were looking for one person who can take a feature from a one-line idea to something live in production — UI, API, data, deploy — because they think in whole systems, ship fast, and use AI as a force multiplier instead of a novelty.

If you’ve spent the last year building Claude, agents, and AI workflows into how you actually work — and you’re shipping 5–10x what you used to — this is for you. If “AI-native” is a line on your rsum but not a habit, it isn’t.

We work hard here: roughly 12 hours a day, 6 days a week. We’re saying that up front because it’s the truth and we’d rather you self-select than be surprised. This suits people in builder mode who want equity-grade ownership and the speed that comes with it. It does not suit people optimizing for balance right now, and that’s a completely valid choice — just not this role.

What you’ll own

You own features end to end — from the pixel a user clicks to the row it writes in the database. No hand-offs, no “that’s a frontend/backend problem.”

- Build user-facing product: clean, fast, responsive interfaces that feel good to use.
- Build the backend behind them: APIs, business logic, data models, integrations.
- Wire in AI features — LLM calls, retrieval, agents, MCP tools — as first-class parts of the product, not bolt-ons.
- Ship it yourself: deploy, monitor, fix. You own the feature in production, not just in the PR.
- Make product and architecture calls and live with them. You decide, you build,



you’re accountable for the outcome.

How we expect you to work (the AI-native part)

This is the differentiator and we’re serious about it.

- You use Claude / AI agents / orchestrated workflows as a daily tool to compress the work — scaffolding UI and services, writing and reviewing code, debugging, generating tests, automating the repetitive across the whole stack.
- You can build the automation, not just consume it: chaining tools, writing agentic workflows, wiring AI into your dev loop and into the product itself.
- You exercise judgment over the output. AI accelerates you; it doesn’t think for you. You know when to trust it and when to throw the answer away.
- Net effect: you ship at a pace that looks unreasonable to someone working the old way.

Tech stack

What you’ll be working in day to day:

- Frontend: React, Next.js, TypeScript, Tailwind CSS
- Backend: Node.js, Express.js (Next.js API routes / FastAPI where it fits)
- Databases: PostgreSQL (incl. pgvector), Redis
- Vector / embeddings: pgvector, plus dedicated stores — Pinecone, Weaviate, ChromaDB, Qdrant
- AI integration: LLM APIs (Claude et al.), agents, Model Context Protocol (MCP)
- APIs & auth: REST, GraphQL, WebSockets; OAuth2, JWT, rate limiting
- Infra & DevOps: AWS, Docker, CI/CD (GitHub Actions); Kubernetes where needed
- AI / NLP (adjacent): Hugging Face, spaCy, NLTK; vLLM, Ollama, MLflow, Weights & Biases

Must-have skills





- 5+ years shipping production software across the full stack.
- React + Next.js + TypeScript — you build interfaces that are fast, accessible, and don’t look like a default template.
- Node.js + Express.js — strong backend chops: APIs, business logic, integrations.
- PostgreSQL + Redis — data modeling, query performance, caching; you reason about data, not just CRUD it.
- API design & auth — REST and GraphQL, OAuth2/JWT, sensible rate limiting.
- Ship-it-yourself ops — comfortable with AWS, Docker, and CI/CD; you can get your own work to production.
- AI feature integration — you’ve built with LLM APIs, retrieval/vector search, and ideally MCP; you know how to make AI features actually work in a product.
- Startup background — early-stage, small teams, ambiguous specs, real ownership.
- Demonstrated AI-native workflow — concrete examples of using Claude/agents to 10x specific work.

Good-to-have skills

- Design sensibility — you have taste and can make a product feel polished without a designer holding your hand.
- Real-time — WebSockets, gRPC, streaming UIs.
- Python + FastAPI — useful when ML and backend overlap.
- Dedicated vector stores — Pinecone, Weaviate, ChromaDB, Qdrant.
- Kubernetes and deeper infra ownership at scale.
- Mobile — React Native or similar cross-platform experience.
- Model serving & MLOps — vLLM, Ollama, MLflow, Weights & Biases.
- Messaging / streaming — Redis Pub/Sub, RabbitMQ, or Kafka.

What you get

- Real ownership and the autonomy to match — you make the calls on what you build.
- A small, rapid, high-trust team with no bureaucracy between you and shipping.
- The chance to build the product from the ground up rather than inherit someone else’s.

📌 Founding Full-Stack Engineer (AI-Native) (Bengaluru)
🏢 withRemote Solutions
📍 Bengaluru