Dilip Kumar · Backend & AI Engineer

01About

A bit about me

I studied computer applications at Kurukshetra University in Haryana and joined my first engineering team in June 2024, before I graduated. Since then I've spent two years at early-stage startups, owning auth, payments and AI features end to end.

I care about systems that behave predictably under load, APIs that are boring to integrate with, and AI features that can show their evidence. Next, I want a team with larger scale and stronger engineering practices. Meanwhile I practice DSA on NeetCode and LeetCode and work through system design.

Education

BCA, Kurukshetra University

Govt. College Chhachhrauli · 2022 to 2025

Recognition

2nd place, state-level exhibition (150+ colleges)

College Roll of Honour

Experience

2 years, backend & AI

Stryv.ai · NexGen Elit · since June 2024

02Experience

Where I've shipped

Jul 2025 to Present

Hyderabad

Python
FastAPI
PostgreSQL
pgvector
AWS
JWT

Full-Stack Engineer @ Stryv.ai

Backend and AI features for a vendor-compliance platform.

Building the AI automation module: hybrid vector + keyword retrieval on PostgreSQL/pgvector, cross-encoder reranking, verbatim-quote validation, and async pipelines with human-in-the-loop approval. See how it works
Built JWT authentication with protected routes, plus OTP password recovery: hashed, expiring OTPs with resend limits and protection against repeated attempts.
Contributed to an AWS document-verification pipeline that processed 160K documents in a month at ~90% verification accuracy.
Own the backend for assessment workflows: response management, category progress tracking and trust-score calculation.
Developed a CRM for sales, leads and customer interactions serving 100K+ users, as part of a 20+ person cross-functional team.

Jun 2024 to Jul 2025

Remote

Node.js
Express
Razorpay
REST APIs
Google Meet

Full-Stack Engineer @ NexGen Elit

My first engineering team, joined before I graduated.

Built a job-portal backend where recruiters post roles and students apply through skill-based assessments, with a dual-sided subscription revenue model.
Integrated Razorpay for student test payments and recruiter job-posting subscriptions.
Built the Node.js/Express backend for a virtual fitness platform: course browsing, an interactive dashboard and integrated Google Meet sessions.

03Work

Systems you can step through

Grounded RAG

An AI module that only accepts an answer it can back with a verbatim quote from the source document.

Question → keyword search + vector search (pgvector) → cross-encoder rerank → LLM draft with quote → verbatim-quote check → human approval.

Hybrid retrieval. Vectors catch paraphrases. Keyword search catches the exact clause names and numbers that embeddings blur.
Rerank before generating. A cross-encoder scores every (question, passage) pair, so the strongest evidence reaches the model first.
Verify, then involve a human. A quote that isn't in the source verbatim fails validation. Validated answers still wait for human approval.

The AI automation module of a vendor-compliance platform: retrieval, reranking, quote validation and an async approval pipeline, in FastAPI on PostgreSQL with pgvector.

Jugaad Link

A URL shortener with Redis-cached redirects, password-protected and expiring links, and per-link analytics.

Live Backend Frontend

Browser → Gin API → Redis (hit: 302 redirect) or PostgreSQL (miss: rule checks, 302, then cache).

Cache only plain links. Password, expiry and click-limit rules must run on every visit. Caching those redirects would silently bypass them.
Record clicks asynchronously. Analytics never sits on the redirect's critical path.
Fail to a friendly page. Disabled, expired and over-limit links redirect to an explanation instead of a bare error.

A Go (Gin, GORM) API on PostgreSQL and Redis with JWT auth, custom slugs, QR codes, guest sessions, a Chrome extension, and click analytics by device, browser, country and referrer. Next.js frontend.

Atlas

A multi-tenant Slack and GitHub assistant: OAuth 2.0, per-workspace webhooks, and a Gemini agent that calls tools.

Code

Slack event → FastAPI → tenant lookup and token decryption in PostgreSQL → Gemini function call → GitHub tool → reply in thread.

Encrypt provider tokens at rest. Slack and GitHub tokens are Fernet-encrypted in PostgreSQL and decrypted only for the tenant that sent the event.
Rotate refresh tokens. They're stored hashed, rotated on every refresh and kept in HTTP-only cookies.
Modular monolith first. One deployable with clear module boundaries (auth, integrations, orchestrator), to split only when scale asks for it.

A FastAPI modular monolith with a Next.js 15 dashboard: OAuth 2.0 login (Google, GitHub, Slack), organization and workspace tenancy, per-tenant webhook ingestion, and a Gemini orchestrator with function calling and a tool dispatcher. PostgreSQL via async SQLAlchemy and Alembic.

ContriHub

Helps developers find beginner-friendly open-source projects, with AI repo explanations and learning roadmaps.

Live Code

Next.js → Go API → Redis rate limit → Redis cache or GitHub API → Groq LLM → 200, or 429 when the limit is hit.

Rate-limit every AI endpoint. Redis limits by IP and by token, so one client can't burn the LLM budget or the GitHub quota.
Cache the GitHub proxy. Repeat lookups are served from Redis instead of spending GitHub API calls.

A Go (Gin, GORM) backend on PostgreSQL and Redis: GitHub OAuth, a caching GitHub API proxy, Groq-powered repo explanations, roadmaps and project matching, and persistent AI chat history. Next.js frontend with filters for language, labels like good-first-issue, topics and stars.

Also built

A prototype, daily practice, and everything else.

Prototype

Document extraction pipeline

Serverless OCR + LLM extraction on AWS: Textract for OCR, Bedrock for structured fields. It was never deployed to production.

Python
Textract
Bedrock

Practice

DSA in C++

Regular NeetCode and LeetCode practice, with every submission public.

Submissions

Everything else

On GitHub

Earlier projects, experiments and the source of this site.

Dilip-Kashyp

04Skills

Every skill, with proof

Languages

Backend

AI & retrieval 1.5y

Data & cloud

Backend patterns

Frontend

05Ask

Interview my resume

A tiny retrieval engine that runs entirely in your browser, over facts I wrote about myself. No LLM and no API key. If it can't find a grounded answer, it says so instead of guessing.

1
Tokenize your question and fix typos against the vocabulary
2
Score 50 hand-written facts with BM25
3
Blend in trigram similarity for fuzzy matches
4
Below the confidence threshold? Say “I don't know”

resume.bot

answers only from Dilip's resume

BM25 + trigram

Hi! Ask me about Dilip's experience, projects, stack or availability. Try a suggestion below or type your own question.

06Contact

Have a backend or AI role in mind? Let's talk.

info@dilipkashyap.in

Usually replies within 24 hours
Hyderabad, India · IST
Open to Bengaluru, remote or relocation

LinkedIn GitHub

Prefer JSON? curl it

dilipkashyap.in/api

$ curl -s dilipkashyap.in/api/me.json

200 OK · application/json

{
  "name": "Dilip Kumar",
  "role": "Backend & AI Engineer",
  "experience_years": 2,
  "current": {
    "title": "Full-Stack Engineer",
    "company": "Stryv.ai",
    "since": "2025-07"
  },
  "location": "Hyderabad, India",
  "open_to": ["Backend Engineer", "AI Engineer", "Full-Stack Engineer"],
  "work_locations": ["Hyderabad", "Bengaluru", "Remote"],
  "focus": ["APIs & auth", "Caching & rate limiting", "RAG pipelines"]
}

Real static JSON served by this site. Try it in your terminal.