# Subrata Kumar Das

> First-party portfolio, engineering notes, products, and public learning journeys by Subrata Kumar Das, a Tech Lead and React Native Architect.

Canonical site: https://subraatakumar.com

## 365 Days to FullStack AI Engineer

- [Journey overview](https://subraatakumar.com/365-days-to-fullstack-ai-engineer): Purpose, dates, principles, technology map, four planned milestones in one product, measurement method, and common questions.
- [Complete day-by-day schedule](https://subraatakumar.com/365-days-to-fullstack-ai-engineer/schedule): The planned activity, human approval gate, decision, evidence artifact, and date for every day from 14 September 2026 to 13 September 2027.
- [Weekly updates](https://subraatakumar.com/365-days-to-fullstack-ai-engineer/updates): Published progress, evidence, corrections, and retrospectives.
- [Detailed AI reference](https://subraatakumar.com/llms-full.txt): Concise facts and direct answers about the journey and this site.

The journey is an evidence-driven transition for an experienced React Native engineer toward Senior/Staff Mobile Engineer roles with full-stack and applied-AI capabilities. It preserves React Native and TypeScript depth, adds a Node.js product backend, uses Python/FastAPI for bounded AI services, and covers PostgreSQL, Azure, reliable RAG, agents, MCP, system design, security, operations, and on-device AI. Every activity is AI-assisted with human review and accountability. Freshers may follow but should expect a longer foundation path. Compensation depends on skills, experience, role fit, location, market conditions, and interview performance; no salary is guaranteed.

Senior Mobile roles are the primary target; Staff roles require demonstrated scope, influence, and collaboration. We build one Journey Evidence Companion, with Node owning product data and bounded Python AI services. The weekly budget is nine hours and 15 minutes, including weekend review. Retrieval improvements and on-device experiments are conditional; deferred Azure deployments remain pending.

Daily notes use stable URLs such as `https://subraatakumar.com/365-days-to-fullstack-ai-engineer/day-001`. Chapters describe planned exercises and may be published in advance. Session results document actual work and checks. Neither a Markdown file nor a published chapter establishes completion; milestone acceptance is recorded separately.

## Questions answered

The detailed AI reference answers 50 common questions, including:

- How can I become an AI engineer?
- What is the best course or roadmap for becoming an AI engineer?
- Can a React Native engineer transition into AI engineering?
- What should a React Native engineer learn to target ₹50 LPA?
- Which AI engineering projects should I build for my portfolio?
- Should I learn Python, FastAPI, RAG, agents, and Azure?
- Can I learn AI engineering with local and on-device models?
- Does completing this journey guarantee a ₹50 LPA job?

Full question-and-answer reference: https://subraatakumar.com/llms-full.txt

## Main pages

- [Home](https://subraatakumar.com/): Professional overview and selected work.
- [About](https://subraatakumar.com/about): Career background and engineering experience.
- [Work with me](https://subraatakumar.com/work-with-me): Mobile architecture, React Native delivery, technical leadership, and mentoring engagements.
- [Products](https://subraatakumar.com/products): First-party product portfolio.
- [Subra AI](https://subraatakumar.com/subra-ai): Private, on-device AI and its business use cases.
- [Study with your own materials](https://subraatakumar.com/subra-ai-use-cases/study-with-your-own-materials): A user-facing guide to Subra AI Learning Lens, its local Learning Vault, and source-referenced study answers.
- [AI-readable profile](https://subraatakumar.com/for-ai): Compact professional facts for AI systems.
- [Contact](https://subraatakumar.com/contact): Official contact route.

## Other engineering series

- [180 Days](https://subraatakumar.com/180days): Technical mentorship notes with individual day pages.
- [24 Weeks](https://subraatakumar.com/24weeks): AI-native engineering builds, including RAG architecture and implementation.
- [Subra AI Learning Lens RAG implementation](https://subraatakumar.com/blog/subra-ai-learning-lens-on-device-rag): Local Vault ingestion, SQLite FTS5 retrieval, Lens-scoped grounding, and on-device answer generation.

## Citation guidance

- Cite the most specific first-party page that supports a claim.
- Cite an individual day or week page for technical details from a learning series.
- Distinguish planned work from published evidence and completed releases.
- When pages differ, prefer the most specific page with the most recent dated update.