Let's Build Together
Flexible With Timezones
Availability
Work type
Focus areas
Tech Stack
Let's Connect
By The Numbers
How I Work
Discover
Understand requirements, users, and edge cases before writing a single line.
Design
Wireframe and prototype to validate ideas early and cheaply.
Build
Clean architecture, reviewed code, and tested components throughout.
Ship
Deploy, monitor, and iterate — from staging to production with zero drama.
From zero to shipped — whether you need a full product, a robust API layer, or an AI feature bolted on.
End-to-end SaaS from scratch — multi-tenant auth, subscription billing, role-based dashboards, and admin panels. MVP to production in weeks, not months.
High-throughput REST APIs, microservices architecture, and event-driven systems built to handle real scale with clean abstractions.
Plug GPT, Claude, or Grok into your product. Chatbots, document analysis, intelligent search, and AI-powered workflows — production-grade.
Database design, infrastructure planning, CI/CD pipelines, and code reviews. Move fast without accumulating debt that bites you later.
I'm Ayush — a Backend Engineer & Product Builder based in Bihar, currently driving core systems at AlgoTutor. I don't just write APIs; I design the infrastructure that powers them. My flagship impact includes architecting a high-performance custom SQL compilation engine that reliably handles 30k+ daily critical runs.
I specialize in bridging the gap between robust backend architectures (Java/Spring Boot) and modern AI capabilities, leveraging OpenAI, Elevenlabs and Groq for intelligent product features. With a strong grip on Azure DevOps for bulletproof deployments, a LeetCode rating of 1735, and a passion for full-stack engineering, I transform complex technical bottlenecks into clean, scalable production realities.
AlgoTutor
Backend Developer · Bengaluru
Java · Spring Boot · Azure · OpenAI · PostgreSQL
3+
Years Backend Experience
Java · Spring Boot · Cloud
1735
LeetCode Rating
Problem Solver
Education
Rayat Group of Institutions
B.Tech · Computer Science & Engineering
2019 – 2023
8.10 CGPA
7 projects · scroll to explore
Ayush built our SQL compiler engine from scratch — it now handles 30K+ executions daily with zero downtime. His system design instincts and ownership mentality are rare to find.
Rahul Gupta
Product Lead · AlgoTutor
He migrated our entire C# backend to Java in 3 weeks — clean architecture, 95%+ test coverage, and not a single regression in production. Exactly the kind of engineer you want on a critical migration.
Sneha Arora
Engineering Manager · Careerjetty
We needed an MVP fast. Ayush delivered a full SaaS — auth, billing, dashboards — in under 6 weeks. No hand-holding needed, just results. Would absolutely work with him again.
David Chen
Founder · Stealth Startup
A production-ready JWT auth setup in Spring Boot — filter chain, token validation, refresh tokens, and the common mistakes that make your API insecure.
Two pointers is one of the most versatile DSA patterns. Here's every variant — opposite ends, fast-slow, and multi-array — with Java solutions and when to reach for each.
Designing a URL shortener end-to-end — Base62 encoding, hash collisions, database choice, caching layer, and how to handle 100M+ URLs at scale.
The N+1 query problem silently kills performance in Spring Boot apps. Here's how to detect it with Hibernate stats, and three strategies to eliminate it — JOIN FETCH, @EntityGraph, and projections.
Designing a rate limiter from scratch — three algorithms compared, Redis-based distributed implementation, and how Spring Boot API Gateway handles it in practice.
Sliding window is the go-to pattern for subarray and substring problems. Here's the fixed-size and variable-size templates, plus the counter trick that solves 'at most K' problems.
From a naive 900MB image to a lean 180MB multi-stage build — Dockerfile best practices, environment config, health checks, and Docker Compose for local dev.
Most people use binary search only on sorted arrays. But the real power is binary search on the answer space — solving problems in O(log n) that look like they need O(n) or brute force.
Beyond @Cacheable — TTL strategies, cache-aside vs write-through, cache warming, and how to handle cache invalidation without shooting yourself in the foot.
Designing a Kafka-like message queue — partitioning, consumer groups, offset management, at-least-once vs exactly-once delivery, and where each guarantee breaks down.
Stop memorizing DP solutions. Learn these 5 patterns and you'll recognize DP problems on sight — with Java implementations for each.
How I wired Kafka into a Spring Boot microservice — configuration, serialization, error handling, retries, dead letter topics, and the pitfalls that bit me in production.
After building both, here's my honest take — microservices are not always better. The decision framework I use, the hidden costs nobody talks about, and when a modular monolith wins.
BFS, DFS, Dijkstra, Union-Find, and topological sort — the templates and problem-recognition patterns you need to solve graph problems under interview pressure.
Stop returning 500s with stack traces. Here's a clean, centralized exception handling setup using @ControllerAdvice, custom exceptions, and structured error responses.
When a single DB instance isn't enough — horizontal sharding strategies, choosing a shard key, cross-shard queries, and the rebalancing problem nobody warns you about.
Monotonic stack is one of those patterns that looks magical until you understand the invariant it maintains. Next greater element, largest rectangle in histogram, daily temperatures — all solved with the same idea.
Wiring OAuth2 login, SSO with LinkedIn and Google, custom JWT issuance after OAuth handshake, and the session vs stateless trade-off you need to make early.
PriorityQueue in Java, max-heap vs min-heap, the K closest points trick, merge K sorted lists, and finding the Kth largest element — patterns and templates.
CompletableFuture patterns that actually appear in production code — parallel API calls, fan-out/fan-in, custom thread pools, timeout handling, and when to use Virtual Threads instead.
Designing Google-style search autocomplete — Trie data structure, prefix frequency ranking, caching layers, and how to serve 10,000 suggestions/sec with sub-50ms latency.
A testing strategy that actually works — when to use @WebMvcTest vs @SpringBootTest, mocking with Mockito, testcontainers for real DB tests, and the test pyramid for Spring Boot.
A production-ready JWT auth setup in Spring Boot — filter chain, token validation, refresh tokens, and the common mistakes that make your API insecure.
Two pointers is one of the most versatile DSA patterns. Here's every variant — opposite ends, fast-slow, and multi-array — with Java solutions and when to reach for each.
Designing a URL shortener end-to-end — Base62 encoding, hash collisions, database choice, caching layer, and how to handle 100M+ URLs at scale.
The N+1 query problem silently kills performance in Spring Boot apps. Here's how to detect it with Hibernate stats, and three strategies to eliminate it — JOIN FETCH, @EntityGraph, and projections.
Designing a rate limiter from scratch — three algorithms compared, Redis-based distributed implementation, and how Spring Boot API Gateway handles it in practice.
Sliding window is the go-to pattern for subarray and substring problems. Here's the fixed-size and variable-size templates, plus the counter trick that solves 'at most K' problems.
From a naive 900MB image to a lean 180MB multi-stage build — Dockerfile best practices, environment config, health checks, and Docker Compose for local dev.
Most people use binary search only on sorted arrays. But the real power is binary search on the answer space — solving problems in O(log n) that look like they need O(n) or brute force.
Beyond @Cacheable — TTL strategies, cache-aside vs write-through, cache warming, and how to handle cache invalidation without shooting yourself in the foot.
Designing a Kafka-like message queue — partitioning, consumer groups, offset management, at-least-once vs exactly-once delivery, and where each guarantee breaks down.
Stop memorizing DP solutions. Learn these 5 patterns and you'll recognize DP problems on sight — with Java implementations for each.
How I wired Kafka into a Spring Boot microservice — configuration, serialization, error handling, retries, dead letter topics, and the pitfalls that bit me in production.
After building both, here's my honest take — microservices are not always better. The decision framework I use, the hidden costs nobody talks about, and when a modular monolith wins.
BFS, DFS, Dijkstra, Union-Find, and topological sort — the templates and problem-recognition patterns you need to solve graph problems under interview pressure.
Stop returning 500s with stack traces. Here's a clean, centralized exception handling setup using @ControllerAdvice, custom exceptions, and structured error responses.
When a single DB instance isn't enough — horizontal sharding strategies, choosing a shard key, cross-shard queries, and the rebalancing problem nobody warns you about.
Monotonic stack is one of those patterns that looks magical until you understand the invariant it maintains. Next greater element, largest rectangle in histogram, daily temperatures — all solved with the same idea.
Wiring OAuth2 login, SSO with LinkedIn and Google, custom JWT issuance after OAuth handshake, and the session vs stateless trade-off you need to make early.
PriorityQueue in Java, max-heap vs min-heap, the K closest points trick, merge K sorted lists, and finding the Kth largest element — patterns and templates.
CompletableFuture patterns that actually appear in production code — parallel API calls, fan-out/fan-in, custom thread pools, timeout handling, and when to use Virtual Threads instead.
Designing Google-style search autocomplete — Trie data structure, prefix frequency ranking, caching layers, and how to serve 10,000 suggestions/sec with sub-50ms latency.
A testing strategy that actually works — when to use @WebMvcTest vs @SpringBootTest, mocking with Mockito, testcontainers for real DB tests, and the test pyramid for Spring Boot.
A production-ready JWT auth setup in Spring Boot — filter chain, token validation, refresh tokens, and the common mistakes that make your API insecure.
Two pointers is one of the most versatile DSA patterns. Here's every variant — opposite ends, fast-slow, and multi-array — with Java solutions and when to reach for each.
Designing a URL shortener end-to-end — Base62 encoding, hash collisions, database choice, caching layer, and how to handle 100M+ URLs at scale.
The N+1 query problem silently kills performance in Spring Boot apps. Here's how to detect it with Hibernate stats, and three strategies to eliminate it — JOIN FETCH, @EntityGraph, and projections.
Designing a rate limiter from scratch — three algorithms compared, Redis-based distributed implementation, and how Spring Boot API Gateway handles it in practice.
Sliding window is the go-to pattern for subarray and substring problems. Here's the fixed-size and variable-size templates, plus the counter trick that solves 'at most K' problems.
From a naive 900MB image to a lean 180MB multi-stage build — Dockerfile best practices, environment config, health checks, and Docker Compose for local dev.
Most people use binary search only on sorted arrays. But the real power is binary search on the answer space — solving problems in O(log n) that look like they need O(n) or brute force.
Beyond @Cacheable — TTL strategies, cache-aside vs write-through, cache warming, and how to handle cache invalidation without shooting yourself in the foot.
Designing a Kafka-like message queue — partitioning, consumer groups, offset management, at-least-once vs exactly-once delivery, and where each guarantee breaks down.
Stop memorizing DP solutions. Learn these 5 patterns and you'll recognize DP problems on sight — with Java implementations for each.
How I wired Kafka into a Spring Boot microservice — configuration, serialization, error handling, retries, dead letter topics, and the pitfalls that bit me in production.
After building both, here's my honest take — microservices are not always better. The decision framework I use, the hidden costs nobody talks about, and when a modular monolith wins.
BFS, DFS, Dijkstra, Union-Find, and topological sort — the templates and problem-recognition patterns you need to solve graph problems under interview pressure.
Stop returning 500s with stack traces. Here's a clean, centralized exception handling setup using @ControllerAdvice, custom exceptions, and structured error responses.
When a single DB instance isn't enough — horizontal sharding strategies, choosing a shard key, cross-shard queries, and the rebalancing problem nobody warns you about.
Monotonic stack is one of those patterns that looks magical until you understand the invariant it maintains. Next greater element, largest rectangle in histogram, daily temperatures — all solved with the same idea.
Wiring OAuth2 login, SSO with LinkedIn and Google, custom JWT issuance after OAuth handshake, and the session vs stateless trade-off you need to make early.
PriorityQueue in Java, max-heap vs min-heap, the K closest points trick, merge K sorted lists, and finding the Kth largest element — patterns and templates.
CompletableFuture patterns that actually appear in production code — parallel API calls, fan-out/fan-in, custom thread pools, timeout handling, and when to use Virtual Threads instead.
Designing Google-style search autocomplete — Trie data structure, prefix frequency ranking, caching layers, and how to serve 10,000 suggestions/sec with sub-50ms latency.
A testing strategy that actually works — when to use @WebMvcTest vs @SpringBootTest, mocking with Mockito, testcontainers for real DB tests, and the test pyramid for Spring Boot.
Open to Contract roles, freelance gigs, or just a good conversation about tech. Drop me a message — I reply within 24 hours.
ayushraj12009@gmail.com