AI-Driven Product Engineer Intern
At Neural City(www.neuralcity.in), we build real-world systems involving AI, geospatial intelligence, street-level visual data, telemetry pipelines, and operational platforms for cities and governance workflows.
This is not a “build another CRUD dashboard” internship. You’ll work on products that interact with maps, cameras, videos, GPS streams, APIs, and messy real-world datasets. We are looking for builders who enjoy complexity, ownership, rapid experimentation, and learning by shipping.
Location: Remote
Duration: 4 to 6 Months
Stipend:
Tentatively between ₹8,000 to ₹12,000 per month.
Higher for candidates with suitable job and cultural fit.
What You’ll Work On
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Build scalable full-stack applications across web, backend, mobile, GIS, and AI-assisted workflows
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Develop APIs, asynchronous services, media-processing systems, telemetry pipelines, and operational dashboards
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Work on React/Next.js frontends, FastAPI backends, React Native mobile applications, and geospatial interfaces
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Contribute to AI-assisted engineering workflows involving coding agents, OCR pipelines, multimodal systems, and intelligent automation
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Build systems involving street imagery, GPS traces, maps, infrastructure data, and operational analytics
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Participate in rapid prototyping, experimentation, debugging, performance optimization, and production-oriented engineering workflows
Technologies You May Work With
React, Next.js, FastAPI, Python, React Native, PostgreSQL/PostGIS, Redis, Docker, Leaflet.js, Claude API, LangChain, OCR pipelines, GIS systems, vector databases, telemetry systems, and asynchronous architectures.
What You’ll Learn
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How production-grade engineering systems are built beyond tutorials and toy projects
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Modern AI-native engineering workflows involving coding agents, automation, retrieval systems, and multimodal AI
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How geospatial systems, telemetry, street imagery, and operational city data become usable intelligence platforms
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Systems thinking around scalability, reliability, asynchronous workflows, observability, and infrastructure design
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How startups prototype, ship, iterate, and learn quickly under real operational constraints
Ideal Candidate
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Strong engineering fundamentals and ability to learn unfamiliar systems quickly
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Comfortable with ambiguity, debugging, experimentation, and ownership
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Interested in AI systems, scalable engineering, GIS, backend systems, or modern product infrastructure
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Builder mindset with curiosity to work across frontend, backend, infrastructure, and AI workflows
This is a hands-on role for people who want to build real systems, not just discuss them.