RFC-KRISH-001 Β Β·Β Status: Production Β Β·Β Region: India β worldwide Β Β·Β Open to: new projects & remote roles
01 whoami Β· 02 architecture Β· 03 changelog Β· 04 deployments Β· 05 dependencies Β· 06 telemetry Β· 07 signed artifacts Β· 08 open ports
![]() GET /api/v1/krish200 OK |
Design principle. Code is poetry, systems are symphonies, and great software is the intersection of engineering excellence and user delight.
How a problem moves through me, drawn the way I'd draw any other system.
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flowchart LR
P([Problem]):::in --> M{{Measure first}}
M --> D[Design<br/>RBAC from the first schema]
D --> B[Build<br/>Next.js Β· Node Β· Python]
B --> E[[Event bus<br/>Kafka Β· Argo]]
E --> AI[AI layer<br/>SageMaker Β· Bedrock Β· STT/TTS]
E --> DB[(Mongo Β· Redis<br/>Postgres Β· Elastic)]
AI --> S[Ship<br/>Docker Β· K8s Β· CI/CD]
DB --> S
S --> U([Real users]):::out
U -. feedback .-> M
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| SLO | Principle | Reference |
|---|---|---|
p0 |
Production over demos: AI that ships and holds up under real users | Case study: Voice AI, speech in, speech out |
p1 |
Measure, then optimise: numbers before opinions | Case study: a secure, fast API platform for fintech |
p2 |
Security is architecture: access control from the first schema | Blog: RBAC done right |
p3 |
Automate the path to prod: releases should be boring | Blog: Zero-downtime deploys |
$ git log --oneline --graph career
* (HEAD -> ironbook-ai) feat(ai): manage agent lifecycles on AWS SageMaker & Bedrock
* feat(voice): ship speech-to-text and voice features end to end
* feat(pipeline): event-driven async systems on Kafka
* feat(migration): large-scale data migrations with Argo Workflows on Kubernetes
|
* feat(gov-tech): media monitoring for 60 Government of India ministries
* + crawlers across 200+ newspapers, YouTube and X
* + STT / TTS APIs and prompt-engineered AI layer
|
* feat(security): RBAC with JWT and AWS IAM across frontend, backend, infra
|
* perf(api): architect 350+ APIs
+ MongoDB response time -40%
+ downtime -40%
+ server performance +25%
|
* ci(devops): Docker Β· Kubernetes Β· Jenkins / GitLab CI
+ deployment time -40%
+ delivery speed +40β50%
|
* init: B.Tech CSE, Lovely Professional University (2019 β 2023)| Service | What it does | Stack | Status |
|---|---|---|---|
| StockX AI Portal | Live pricing, AI market recaps and sentiment-tagged news | Next.js Β· AI recaps Β· live market data | π’ live |
| LMS Portal | Production-level EdTech platform for courses and learners | Next.js 15 Β· TypeScript Β· MongoDB | π’ live |
| Pathfinding Visualizer | Dijkstra, A*, BFS and DFS on a live, editable grid | Next.js Β· TypeScript Β· Framer Motion | π’ live |
| SortFusion | Every compare and swap of eight sorting algorithms, visualized | Next.js Β· TypeScript Β· Framer Motion | π’ live |
|
Claude Certified Developer β Foundations sig: verified Β· Credly
|
Claude Certified Associate β Foundations sig: verified Β· Credly
|
More artifacts Β (8)
| Certification | Issuer | |
|---|---|---|
| π₯ | Jumpstart β Publicis Sapient Competitive Coding Event | Publicis Sapient |
| π | ACE Multicloud Network Associate | Aviatrix |
| β | Java Foundations Certification | HackerRank |
| βοΈ | React Redux Training | Cipher Schools |
| π€ | Artificial Intelligence Fundamentals | Invincible Ocean |
| π‘οΈ | Website Hacking / Penetration Testing | Udemy |
| π» | Web Development Bootcamp | Udemy |
| π | Object-Oriented Programming Using Python | E-Box |
$ netstat -krish --listening
PORT SERVICE STATUS
443 portfolio LISTEN β krish-portfolio-six.vercel.app
587 email LISTEN β krishnendughosal999@gmail.com
8080 linkedin LISTEN β in/krish-me
9000 collaboration LISTEN β new projects Β· remote roles$ systemctl status krish.service Β βΒ β active (running) Β Β·Β thanks for visiting β¦






{ "name": "Krishnendu Ghosal", "role": ["Full-Stack Developer", "AI/ML Engineer", "Cloud & DevOps"], "current": { "org": "Ironbook AI", "shipping": ["speech-to-text & voice services", "customer data platforms", "Kafka-driven pipelines on Kubernetes"] }, "experience": { "years": "3+", "companies": 5, "domains": ["Gov-Tech", "Fintech", "B2B Enterprise", "B2C Digital"] }, "learning": ["LLM agents", "RAG", "MLOps", "large-scale system design"], "ask_me_about": ["Next.js", "Node.js", "Python", "Kafka", "Kubernetes", "SageMaker", "Bedrock", "Redis", "MongoDB", "Elasticsearch"] }